数学物理学报, 2026, 46(6): 2349-2370

一类非局部扩散的分布时滞SVIR 模型的行波解

邱小勤,, 杨赟瑞,*

兰州交通大学数理学院 兰州 730070

Traveling Wave Solutions to a Class of SVIR Model with Distributed Delay and Nonlocal Dispersal

Qiu Xiaoqin,, Yang Yunrui,*

School of Mathematics and Physics, Lanzhou Jiaotong University, Lanzhou 730070

通讯作者: 杨赟瑞, E-mail: lily1979101@163.com

收稿日期: 2025-08-28   修回日期: 2025-12-5  

基金资助: 国家自然科学基金(12361038)
甘肃省基础研究创新群体项目(25JRRA805)

Received: 2025-08-28   Revised: 2025-12-5  

Fund supported: National Natural Science Foundation of China(12361038)
Foundation for Innovative Fundamental Research Group Project of Gansu Province(25JRRA805)

作者简介 About authors

邱小勤,E-mail:xq050621@163.com

摘要

研究了一类非局部扩散的分布时滞SVIR 模型的行波解. 通过上、下解的构造和Schauder 不动点定理、极限理论与 Lyapunov 函数方法建立了该模型行波解的存在性. 特别地, 在验证行波解满足的渐近边界条件时, 由于分布时滞的出现, 使行波解有界性的建立和Lyapunov 函数的构造变得困难, 需要更为细致的分析技术. 此外, 基于渐近传播理论和反证法得到了该模型行波解的不存在性. 这不仅将无时滞和离散时滞SVIR 模型行波解的研究结果推广到了分布时滞情形, 还完善了考虑疫苗接种策略的传染病模型行波解的研究.

关键词: 非局部扩散; 分布时滞; 行波解; 存在性; 不存在性

Abstract

Traveling wave solutions for a class of SVIR model with distributed delay and nonlocal dispersal are considered. By the construction of upper and lower solutions and with the help of Schauder's fixed-point theorem, limit theory, analytical techniques, and Lyapunov function methods, the existence of traveling wave solutions for this model is established. Particularly, it is essential to use analytical techniques more detailed for testifying the asymptotic boundary conditions of traveling waves since it becomes more difficult for the boundedness of traveling waves and the construction of Lyapunov functions for the presence of distributed delay in the model. Moreover, the non-existence of traveling waves is obtained by asymptotic spreading theory and a contradiction argument. Therefore, the results on traveling waves for delay-free and discrete time-delay SVIR models are not only extended to the case of distributed delay, but the research of traveling waves in vaccination-stratified epidemic models is enriched and completed.

Keywords: nonlocal dispersal; distributed delay; traveling wave solutions; existence; nonexistence

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本文引用格式

邱小勤, 杨赟瑞. 一类非局部扩散的分布时滞SVIR 模型的行波解[J]. 数学物理学报, 2026, 46(6): 2349-2370

Qiu Xiaoqin, Yang Yunrui. Traveling Wave Solutions to a Class of SVIR Model with Distributed Delay and Nonlocal Dispersal[J]. Acta Mathematica Scientia, 2026, 46(6): 2349-2370

1 引言

传染病学中, 病原体通过宿主的空间迁移和个体间接触发生扩散. 因此, 考虑不同人群的流动和传染源的扩散等因素建立的传染病模型可以刻画疾病的发展态势. 例如, 总人口数非恒定、具有标准发生率的 Laplace 扩散 SIR 模型[1]

$\begin{equation} \begin{cases} \frac{\partial S(x,t)}{\partial t}= d_1 \frac{\partial^2 S(x,t)}{\partial x^2} - \frac{\beta S(x,t) I(x,t)}{N(x,t)}, \\[5pt] \frac{\partial I(x,t)}{\partial t}= d_2 \frac{\partial^2 I(x,t)}{\partial x^2} + \frac{\beta S(x,t) I(x,t)}{N(x,t)} - \gamma I(x,t) - \delta I(x,t), \\[5pt] \frac{\partial R(x,t)}{\partial t}= d_3 \frac{\partial^2 R(x,t)}{\partial x^2} + \gamma I(x,t). \end{cases} \end{equation}$

其中, $N(x,t)=S(x,t)+I(x,t)+R(x,t)$ 为总人口数, $S(x,t),\ I(x,t)$$R(x,t)$ 分别表示$x$ 位置$t$ 时刻易感者、已感者者和恢复者的密度, $d_i > 0 \ (i=1,2,3)$ 为扩散率, $\beta$ 为感染率, $\gamma$ 是已感者的康复率, $\delta$ 是已感者的死亡率.

然而, 当传染病的扩散与传播不只限于当前位置, 还与相邻位置甚至整个空间有关时、即非局部扩散, 通常用如下积分项

$\begin{equation} \mathcal{J}*u(x,t)-u(x,t)=\int_{\mathbb{R}} \mathcal{J}(x-y)u(y,t)\mathrm{d}y-u(x,t) \end{equation}$

来表示, 其中核函数$ \mathcal{J}(\cdot)$ 满足 $ \int_{\mathbb{R}} \mathcal{J}(x - y) u(y,t)\mathrm{d}y$ 表示个体从其他空间位置到达$x$ 位置的概率分布. 基于此, 越来越多的人开始关注 (时滞) 非局部扩散模型[2,3,4,5,6,7]. 例如, 具有标准发生率的非局部扩散 SIR 模型[6]

$\begin{equation} \begin{cases} \frac{\partial S(x,t)}{\partial t}= d_1 ( \mathcal{J} * S(x,t) - S(x,t)) - \frac{\beta S(x,t) I(x,t)}{S(x,t) + I(x,t)}, \\[5pt] \frac{\partial I(x,t)}{\partial t}= d_2 ( \mathcal{J} * I(x,t) - I(x,t)) + \frac{\beta S(x,t) I(x,t)}{S(x,t) + I(x,t)} - \gamma I(x,t), \\[5pt] \frac{\partial R(x,t)}{\partial t}= d_3 ( \mathcal{J} * R(x,t) - R(x,t)) + \gamma I(x,t) \end{cases} \end{equation}$

和具有非线性发生率的时滞非局部扩散 SIR 模型[7]

$\begin{equation} \begin{cases} \frac{\partial S(x,t)}{\partial t} = d_1 \bigl( \mathcal{J} * S(x,t) - S(x,t)\bigr) - f\bigl(S(x,t)\bigr) g\bigl(I(x,t - \tau)\bigr), \\[4pt] \frac{\partial I(x,t)}{\partial t} = d_2 \bigl( \mathcal{J} * I(x,t) - I(x,t)\bigr) + f\bigl(S(x,t)\bigr) g\bigl(I(x,t - \tau)\bigr) - \gamma I(x,t), \\[4pt] \frac{\partial R(x,t)}{\partial t} = d_3 \bigl( \mathcal{J} * R(x,t) - R(x,t)\bigr) + \gamma I(x,t), \end{cases} \end{equation}$

其中 $\tau \geq 0$ 表示传染病的潜伏期.

然而, 潜伏期的长短因人而异, 若其传播不仅与当前位置的状态有关, 还依赖于过去整个历史时期, 常通过分布时滞项 $\int_{0}^{\tau} K(s)I(x,t-s)\mathrm{d}s$ 来体现, 核函数 $K(\cdot) > 0$ 满足

$\int_{0}^{\tau} K(s)\mathrm{d}s = 1,~~ 0 < \tau \leq +\infty.$

因此, 分布时滞传染病模型更符合客观实际[8,9,10,11,12]. 例如, 具有非线性发生率的非局部扩散分布时滞 SI 模型[11]

$\begin{equation} \begin{cases} \frac{\partial S(x,t)}{\partial t}= d_1 \bigl( \mathcal{J} * S(x,t) - S(x,t)\bigr) - \beta S(x,t) \int_{0}^{\tau} f(s) g\bigl(I(x,t - s)\bigr) \, \mathrm{d}s, \\[5pt] \frac{\partial I(x,t)}{\partial t}= d_2 \bigl( \mathcal{J} * I(x,t) - I(x,t)\bigr) + \beta S(x,t) \int_{0}^{\tau} f(s) g\bigl(I(x,t - s)\bigr) \, \mathrm{d}s - \gamma I(x,t) \end{cases} \end{equation}$

和分布时滞 SIR 模型[12]

$\begin{equation} \begin{cases} \frac{\partial S(x,t)}{\partial t} = d_1 \bigl( \mathcal{J} * S(x,t) - S(x,t)\bigr) + \Lambda - \mu S(x,t) - \beta f\bigl(S(x,t), I(x,t)\bigr), \\[4pt] \frac{\partial I(x,t)}{\partial t} = d_2 \bigl( \mathcal{J} * I(x,t) - I(x,t)\bigr) + \beta \int_{0}^{\tau} h(s) f\bigl(S(x,t - s), I(x,t - s)\bigr) \mathrm{d}s \\ - (\mu + \gamma + \alpha) I(x,t), \\ \frac{\partial R(x,t)}{\partial t} = d_3 \bigl( \mathcal{J} * R(x,t) - R(x,t)\bigr) + \gamma I(x,t) - \mu R(x,t). \end{cases} \end{equation}$

此外, 疫苗作为传染病的有效防疫手段之一, 可以有效控制传染病的传播. 例如为了应对流感病毒的传播, 人们通过接种季节性流感疫苗降低了流感的发病率和重症风险. 因此, 研究考虑疫苗接种策略的传染病模型[13,14,15]更具现实意义. 例如, 非局部扩散的分布时滞 SVIR 模型

$\begin{equation} \begin{cases} \frac{\partial u_1(x,t)}{\partial t} = d_1 \bigl( \mathcal{J} * u_1(x,t) - u_1(x,t)\bigr) + \Lambda - \beta_1 u_1(x,t) \int_{0}^{\tau} K(s) u_3(x,t - s) \, \mathrm{d}s \\ - (\alpha + \mu_1) u_1(x,t), \\ \frac{\partial u_2(x,t)}{\partial t} = d_2 \bigl( \mathcal{J} * u_2(x,t) - u_2(x,t)\bigr) - \beta_2 u_2(x,t) \int_{0}^{\tau} K(s) u_3(x,t - s) \, \mathrm{d}s + \alpha u_1(x,t) \\ - (\gamma_1 + \mu_2) u_2(x,t), \\ \frac{\partial u_3(x,t)}{\partial t} = d_3 \bigl( \mathcal{J} * u_3(x,t) - u_3(x,t)\bigr) + \beta_1 u_1(x,t) \int_{0}^{\tau} K(s) u_3(x,t - s) \, \mathrm{d}s \\ + \beta_2 u_2(x,t) \int_{0}^{\tau} K(s) u_3(x,t - s) \, \mathrm{d}s - (\gamma + \mu_3) u_3(x,t), \\ \frac{\partial u_4(x,t)}{\partial t} = d_4 \bigl( \mathcal{J} * u_4(x,t) - u_4(x,t)\bigr) + \gamma_1 u_2(x,t) + \gamma u_3(x,t) - \mu_4 u_4(x,t), \end{cases} \end{equation}$

其中 $u_1(x,t),\ u_2(x,t), u_3(x,t)$$u_4(x,t)$ 分别表示$t$ 时刻$x$ 位置易感者、接种疫苗者、已感者和恢复者的密度, $d_i > 0 \ (i=1,2,3,4)$ 为扩散率, $\Lambda > 0$ 表示易感者的外部输入率, $\beta_1, \beta_2>0$ 分别是易感者和接种疫苗者与已感者之间的感染率, $ \mu_i>0\ (i=1,2,3,4)$ 分别表示易感、接种、已染和治愈者的自然死亡率. $ \alpha>0,\gamma_1>0$$\gamma>0$ 分别为疫苗接种率、接种疫苗的个体获得的免疫率和已感者恢复率.

特别地, 当$K(s)=\delta(s-\tau)$ (这里 $ \delta(\cdot)$ 是 Dirac 函数) 时, 模型(1.7)退化为非局部扩散的离散时滞 SVIR 模型[14]

$\begin{equation} \begin{cases} \frac{\partial S(x,t)}{\partial t} = d_1 \bigl( \mathcal{J} * S(x,t) - S(x,t)\bigr) + \Lambda - \beta_1 S(x,t) I(x,t - \tau) - \alpha S(x,t) - \mu_1 S(x,t), \\ \frac{\partial V(x,t)}{\partial t} = d_2 \bigl( \mathcal{J} * V(x,t) - V(x,t)\bigr) - \beta_2 V(x,t) I(x,t - \tau) + \alpha S(x,t) \\ - (\gamma_1 + \mu_2) V(x,t), \\ \frac{\partial I(x,t)}{\partial t} = d_3 \bigl( \mathcal{J} * I(x,t) - I(x,t)\bigr) + \beta_1 S(x,t) I(x,t - \tau) + \beta_2 V(x,t) I(x,t - \tau) \\ - (\gamma - \mu_3) I(x,t), \\ \frac{\partial R(x,t)}{\partial t} = d_4 \bigl( \mathcal{J} * R(x,t) - R(x,t)\bigr) + \beta_1 S(x,t) I(x,t - \tau) + \gamma_1 V(x,t) + (\gamma - \mu_4) R(x,t). \end{cases} \end{equation}$

传染病模型中, 行波解表示传染波在空间的传播, 若传染波的波速大于或等于个体远离传染源的速度, 则行波解存在, 即传染病能够感染个体, 否则传染病不会感染个体. 因此, 传染病模型行波解的存在性、不存在性及定性性质反映了传染病的传播情况和发展态势. 为此, 越来越多的学者致力于 (时滞) 非局部扩散传染病模型行波解的研究. 例如, Li 和 Yang 等[6]利用 Schauder 不动点和 Laplace 变换研究了具有标准发生率的时滞非局部扩散 SIR 模型 (1.3) 行波解的存在性与不存在性. 2018 年, 邹和吴等[7]将 Li 和 Yang 等的结果[6]推广到具有一般发生率的时滞非局部扩散 SIR 模型(1.4). 此后, Wu 和 Teng 等[12]利用 Schauder 不动点定理、 Lyapunov 函数和渐近传播理论建立了非局部扩散分布时滞 SIR 模型(1.6)行波解的存在性与不存在性.

注意到, 上述工作大多是不考虑疫苗接种策略的 (无) 时滞非局部扩散传染病模型行波解的研究. 2019 年, Zhang 和 Liu[14] 利用上、下解结合 Schauder 不动点定理和 Lyapunov 函数方法建立了考虑疫苗接种策略的离散时滞 SVIR 模型(1.8)行波解的存在性与不存在性. 近来, 李和杨等人[16]利用加权能量方法结合连续延拓方法完善了模型(1.8)单稳行波解的稳定性结果. 但是, 对考虑疫苗接种策略的非局部扩散分布时滞传染病模型行波解的研究还不多见, 受 Wu[12] 和 Zhang[14] 等人工作的启发, 本文试图将 Zhang[14] 对离散时滞 SVIR 模型(1.8)行波解的研究推广到分布时滞 SVIR 模型(1.7), 通过上、下解结合 Schauder 不动点定理、极限理论与 Lyapunov 函数方法建立当基本再生数 $R_0 > 1, \ c \geq c^*$ 时模型(1.7)行波解的存在性. 特别地, 在验证行波解满足的渐近边界条件时, 由于分布时滞的出现, 使行波解有界性的建立和 Lyapunov 函数的构造变得困难, 需要更为细致的分析技术来克服. 此外, 利用渐近传播理论和反证法得到了当 $R_0 > 1, \ 0 < c < c^*$ 时模型(1.7)行波解的不存在性. 基于此, 本文不仅推广了无时滞和离散时滞的 SVIR 模型行波解的研究结果, 还完善了考虑疫苗接种策略的传染病模型行波解的研究.

2 预备知识

首先, 给出本文用到的假设条件:

$(A_{1}) \mathcal{J}(\cdot)\in C^{1}(\mathbb{R})$ 具有紧支集, $ \mathcal{J}(y)= \mathcal{J}(-y)\geq 0,~\int_{\mathbb{R}} \mathcal{J}(y)\mathrm{d}y=1$.

$(A_{2}) K(\cdot)$$[0,\tau)$ 上非负可积, 其中 $\tau>0$, 且 $\int_{0}^{\tau} K(s)\mathrm{d}s = 1$.

由于模型(1.7)的前三个方程中不含$u_4(x,t)$, 故仅需考虑模型

$\begin{equation} \begin{cases} \frac{\partial u_1(x,t)}{\partial t} = d_1 \bigl( \mathcal{J} * u_1(x,t) - u_1(x,t)\bigr) + \Lambda - \beta_1 u_1(x,t) \int_{0}^{\tau} K(s) u_3(x,t - s) \, \mathrm{d}s \\ - (\alpha + \mu_1) u_1(x,t), \\ \frac{\partial u_2(x,t)}{\partial t} = d_2 \bigl( \mathcal{J} * u_2(x,t) - u_2(x,t)\bigr) - \beta_2 u_2(x,t) \int_{0}^{\tau} K(s) u_3(x,t - s) \, \mathrm{d}s + \alpha u_1(x,t)\\ \ - (\gamma_1 + \mu_2) u_2(x,t), \\ \frac{\partial u_3(x,t)}{\partial t} = d_3 \bigl( \mathcal{J} * u_3(x,t) - u_3(x,t)\bigr) + \beta_1 u_1(x,t) \int_{0}^{\tau} K(s) u_3(x,t - s) \, \mathrm{d}s\\ \ + \beta_2 u_2(x,t) \int_{0}^{\tau} K(s) u_3(x,t - s) \, \mathrm{d}s - (\gamma + \mu_3) u_3(x,t). \end{cases} \end{equation}$

不难验证, 模型(2.1) 有无病平衡点$E_0 = (U_{10}, U_{20}, 0) = \left( \frac{\Lambda}{\mu_1 + \alpha}, \frac{\Lambda \alpha}{(\gamma_1 + \mu_2)(\mu_1 + \alpha)}, 0 \right)$ 和满足

$\begin{equation} \begin{cases} \Lambda - \beta_1 U_1^* U_3^* - (\alpha + \mu_1) U_1^* = 0, \\ - \beta_2 U_2^* U_3^* + \alpha U_1^* - (\gamma_1 + \mu_2) U_2^* = 0, \\ \beta_1 U_1^* U_3^* + \beta_2 U_2^* U_3^* - (\gamma + \mu_3) U_3^* = 0 \end{cases} \end{equation}$

的唯一正平衡点$E^* = (U_1^*, U_2^*, U_3^*)$.

模型(2.1)的行波解是指形如$(u_1(x,t),u_2(x,t),u_3(x,t))=(u_1(\xi),u_2(\xi),u_3(\xi))$$\xi=x+ct$ 的解, 其中$\xi\in \mathbb{R}$, $c>0$ 为波速. 因此, 模型(2.1) 的行波系统是

$\begin{equation} \begin{cases} c U_1'(\xi) = d_1 \bigl( \mathcal{J} * U_1(\xi) - U_1(\xi)\bigr) + \Lambda - \beta_1 U_1(\xi) \int_{0}^{\tau} K(s) U_3(\xi - cs) \, \mathrm{d}s - (\alpha + \mu_1) U_1(\xi), \\ c U_2'(\xi) = d_2 \bigl( \mathcal{J} * U_2(\xi) - U_2(\xi)\bigr) - \beta_2 U_2(\xi) \int_{0}^{\tau} K(s) U_3(\xi - cs) \, \mathrm{d}s + \alpha U_1(\xi) - (\gamma_1 + \mu_2) U_2(\xi), \\ c U_3'(\xi) = d_3 \bigl( \mathcal{J} * U_3(\xi) - U_3(\xi)\bigr) + \beta_1 U_1(\xi) \int_{0}^{\tau} K(s) U_3(\xi - cs) \, \mathrm{d}s \\ \ + \beta_2 U_2(\xi) \int_{0}^{\tau} K(s) U_3(\xi - cs) \, ds - (\gamma + \mu_3) U_3(\xi) \end{cases} \end{equation}$

且满足边界条件

$\begin{equation} \lim_{\xi \to -\infty} \bigl(U_1(\xi), U_2(\xi), U_3(\xi)\bigr) = (U_{10}, U_{20}, 0), \\ \lim_{\xi \to +\infty} \bigl(U_1(\xi), U_2(\xi), U_3(\xi)\bigr) = (U_1^*, U_2^*, U_3^*). \end{equation}$

为了建立模型(2.1)行波解的 (不) 存在性, 只需研究行波系统(2.3)解的 (不) 存在性. 为此, 先考虑(2.3)中第三个方程在无病平衡点处的线性化方程

$\begin{equation} \begin{aligned} c U_3'(\xi) &= d_3 \bigl( \mathcal{J} * U_3(\xi) - U_3(\xi)\bigr) + \beta_1 U_{10} \int_{0}^{\tau} K(s) U_3(\xi - cs) \, \mathrm{d}s \\ &\quad + \beta_2 U_{20} \int_{0}^{\tau} K(s) U_3(\xi - cs) \, \mathrm{d}s - (\gamma + \mu_3) U_3(\xi). \end{aligned} \end{equation}$

$U_3(\xi)=\mathrm{e}^{\lambda \xi}$ 代入(2.4), 可得

$\begin{gather*} c \lambda \mathrm{e}^{\lambda \xi} = d_3 \left( \int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{\lambda (\xi - y)} \, \mathrm{d}y - \mathrm{e}^{\lambda \xi} \right) + (\beta_1 U_{10} + \beta_2 U_{20}) \int_{0}^{\tau} K(s) \mathrm{e}^{\lambda (\xi - cs)} \, \mathrm{d}s - (\gamma + \mu_3) \mathrm{e}^{\lambda \xi}. \end{gather*}$

$\Delta(\lambda, c) = d_3 \int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{-\lambda y} \, \mathrm{d}y - (d_3 + \gamma + \mu_3) + (\beta_1 U_{10} + \beta_2 U_{20}) \int_{0}^{\tau} K(s) \mathrm{e}^{-\lambda c s} \, \mathrm{d}s - c \lambda.$

通过计算, 不难得到

$\begin{gather*} \Delta(0, c) = \beta_1 U_{10} + \beta_2 U_{20} - \gamma - \mu_3, \lim_{\substack{c \to +\infty }} \Delta(\lambda, c) = -\infty, \lambda > 0, \\ \left. \frac{\partial \Delta(\lambda, c)}{\partial \lambda} \right|_{(0, c)} = -c - cs (\beta_1 U_{10} + \beta_2 U_{20}) < 0, c > 0, \\ \frac{\partial^2 \Delta(\lambda, c)}{\partial \lambda^2} = d_3 \int_{\mathbb{R}} y^2 \mathcal{J}(y) \mathrm{e}^{-\lambda y} \, \mathrm{d}y + (\beta_1 U_{10} + \beta_2 U_{20}) \int_{0}^{\tau} c^2 s^2 K(s) \mathrm{e}^{-\lambda c s} \, \mathrm{d}s > 0, \\ \frac{\partial \Delta(\lambda, c)}{\partial c} = -(\beta_1 U_{10} + \beta_2 U_{20}) \int_{0}^{\tau} \lambda s K(s) \mathrm{e}^{-\lambda c s} \, \mathrm{d}s - \lambda < 0, \lambda > 0. \end{gather*}$

若基本再生数$R_0 := \frac{\beta_1 U_{10} + \beta_2 U_{20}}{\mu_3 + \gamma} > 1$, 则$\Delta(0, c) = (\mu_3 + \gamma) (R_0 - 1) > 0$, 任意的$ c\in\mathbb{R}$. 从而, 存在$c^*, \lambda^*>0$, 使得$\left. \frac{\partial \Delta(\lambda, c)}{\partial \lambda} \right|_{(\lambda^*, c^*)} = 0$.

引理 2.1$ R_0 = \frac{\beta_1 U_{10} + \beta_2 U_{20}}{\mu_3 + \gamma} > 1 $, 则

(1) 若 $ c = c^* $, 则 $ \Delta(\lambda, c) = 0 $ 有两个相同的正实根 $ \lambda^* $;

(2) 若 $ 0 < c < c^* $, 则 $ \Delta(\lambda, c) > 0 $ 不存在正实根;

(3) 若 $ c > c^* $, 则 $ \Delta(\lambda, c) = 0 $ 有两个相异正实根 $ \lambda_1(c) $$ \lambda_2(c) $.

不难验证 $ 0 < \lambda_c < \lambda^* < \lambda_2(c) $, 其中 $ \lambda_c = \lambda_1(c) $. 下面给出行波系统(2.3)的上下解定义.

定义 2.1 (上下解) 若 $(A_1)-(A_2)$ 成立, 且 $(\overline{U}_1(\xi), \overline{U}_2(\xi), \overline{U}_3(\xi))$$(\underline{U}_1(\xi), \underline{U}_2(\xi), \underline{U}_3(\xi))$ 分别满足

$\begin{equation} \begin{cases} c \overline{U}_1'(\xi) \geq d_1 \bigl( \mathcal{J} * \overline{U}_1(\xi) - \overline{U}_1(\xi)\bigr) + \Lambda - \beta_1 \overline{U}_1(\xi) \int_{0}^{\tau} K(s) \overline{U}_3(\xi - cs) \, \mathrm{d}s - (\alpha + \mu_1) \overline{U}_1(\xi), \\ c \overline{U}_2'(\xi) \geq d_2 \bigl( \mathcal{J} * \overline{U}_2(\xi) - \overline{U}_2(\xi)\bigr) - \beta_2 \overline{U}_2(\xi) \int_{0}^{\tau} K(s) \overline{U}_3(\xi - cs) \, \mathrm{d}s + \alpha \overline{U}_1(\xi) - (\gamma_1 + \mu_2) \overline{U}_2(\xi), \\ c \overline{U}_3'(\xi) \geq d_3 \bigl( \mathcal{J} * \overline{U}_3(\xi) - \overline{U}_3(\xi)\bigr) + \beta_1 \overline{U}_1(\xi) \int_{0}^{\tau} K(s) \overline{U}_3(\xi - cs) \, \mathrm{d}s \\ + \beta_2 \overline{U}_2(\xi) \int_{0}^{\tau} K(s) \overline{U}_3(\xi - cs) \, \mathrm{d}s - (\gamma + \mu_3) \overline{U}_3(\xi) \end{cases} \end{equation}$

$\begin{equation} \begin{cases} c \underline{U}_1'(\xi) \leq d_1 \bigl( \mathcal{J} * \underline{U}_1(\xi) - \underline{U}_1(\xi)\bigr) + \Lambda - \beta_1 \underline{U}_1(\xi) \int_{0}^{\tau} K(s) \underline{U}_3(\xi - cs) \, \mathrm{d}s - (\alpha + \mu_1) \underline{U}_1(\xi), \\ c \underline{U}_2'(\xi) \leq d_2 \bigl( \mathcal{J} * \underline{U}_2(\xi) - \underline{U}_2(\xi)\bigr) - \beta_2 \underline{U}_2(\xi) \int_{0}^{\tau} K(s) \underline{U}_3(\xi - cs) \, \mathrm{d}s + \alpha \underline{U}_1(\xi) - (\gamma_1 + \mu_2) \underline{U}_2(\xi), \\ c \underline{U}_3'(\xi) \leq d_3 \bigl( \mathcal{J} * \underline{U}_3(\xi) - \underline{U}_3(\xi)\bigr) + \beta_1 \underline{U}_1(\xi) \int_{0}^{\tau} K(s) \underline{U}_3(\xi - cs) \, \mathrm{d}s\\ + \beta_2 \underline{U}_2(\xi) \int_{0}^{\tau} K(s) \underline{U}_3(\xi - cs) \, \mathrm{d}s - (\gamma + \mu_3) \underline{U}_3(\xi) \end{cases} \end{equation}$

则称 $(\overline{U}_1(\xi), \overline{U}_2(\xi), \overline{U}_3(\xi))$$(\underline{U}_1(\xi), \underline{U}_2(\xi), \underline{U}_3(\xi))$ 分别为(2.3)的上解和下解.

3 行波解的存在性

本节研究当$R_0 > 1, c \geq c^*$ 时(2.1)行波解的存在性. 首先构造(2.3)的上、下解:

$ \begin{align*} \overline{U}_1(\xi) &= U_{10}, \underline{U}_1(\xi)= \max \left\{ U_{10} - M_1 \mathrm{e}^{\varepsilon_1 \xi}, 0 \right\}, \\ \overline{U}_2(\xi) &= U_{20}, \underline{U}_2(\xi)= \max \left\{ U_{20} - M_2 \mathrm{e}^{\varepsilon_2 \xi}, 0 \right\}, \\ \overline{U}_3(\xi) &= \mathrm{e}^{\lambda_c \xi}, \underline{U}_3(\xi)= \max \left\{ \mathrm{e}^{\lambda_c \xi} \left(1 - M_3 \mathrm{e}^{\varepsilon_3 \xi}\right), 0 \right\}, \end{align*} $

其中 $\varepsilon_1, \varepsilon_2, \varepsilon_3, M_1, M_2$$M_3$ 均为适当的正常数, 它们满足的条件见引理 3.1-3.5. 由于验证上解 $(\overline{U}_1(\xi), \overline{U}_2(\xi), \overline{U}_3(\xi))$ 的证明过程是平凡的 (引理 3.1 和引理 3.2), 故此省略.

引理 3.1 函数 $\overline{U}_3(\xi) = \mathrm{e}^{\lambda_c \xi}$ 满足

$\begin{equation} \begin{split} c \overline{U}_3'(\xi) &\geq d_3 \bigl( \mathcal{J} * \overline{U}_3(\xi) - \overline{U}_3(\xi)\bigr) + \beta_1 \overline{U}_1(\xi) \int_{0}^{\tau} K(s) \overline{U}_3(\xi - cs) \, \mathrm{d}s \\ &\quad + \beta_2 \overline{U}_2(\xi) \int_{0}^{\tau} K(s) \overline{U}_3(\xi - cs) \, \mathrm{d}s - (\gamma + \mu_3) \overline{U}_3(\xi). \end{split} \end{equation}$

引理 3.2 函数 $\overline{U}_1(\xi) = U_{10}$$\overline{U}_2(\xi) = U_{20}$ 满足

$\begin{equation} \begin{cases} c \overline{U}_1'(\xi) \geq d_1 \bigl( \mathcal{J} * \overline{U}_1(\xi) - \overline{U}_1(\xi)\bigr) + \Lambda - \beta_1 \overline{U}_1(\xi) \int_{0}^{\tau} K(s) \underline{U}_3(\xi - cs) \, \mathrm{d}s - (\alpha + \mu_1) \overline{U}_1(\xi), \\ c \overline{U}_2'(\xi) \geq d_2 \bigl( \mathcal{J} * \overline{U}_2(\xi) - \overline{U}_2(\xi)\bigr) - \beta_2 \overline{U}_2(\xi) \int_{0}^{\tau} K(s) \underline{U}_3(\xi - cs) \, \mathrm{d}s + \alpha \overline{U}_1(\xi) - (\gamma_1 + \mu_2) \overline{U}_2(\xi). \end{cases} \end{equation}$

下面验证 $(\underline{U}_1(\xi), \underline{U}_2(\xi), \underline{U}_3(\xi))$ 是(2.3)的下解.

引理 3.3 若存在充分小的数 $\varepsilon_1$ 满足 $0 < \varepsilon_1 < \lambda_c$ 和充分大的正数 $M_1$, 则函数 $\underline{U}_1(\xi) = \max \left\{ U_{10} - M_1 \mathrm{e}^{\varepsilon_1 \xi}, 0 \right\}$ 满足

$\begin{equation} \begin{split} c \underline{U}_1'(\xi) &\leq d_1 \bigl( \mathcal{J} * \underline{U}_1(\xi) - \underline{U}_1(\xi)\bigr) + \Lambda - \beta_1 \underline{U}_1(\xi) \int_{0}^{\tau} K(s) \overline{U}_3(\xi - cs) \, \mathrm{d}s - (\alpha + \mu_1) \underline{U}_1(\xi), \end{split} \end{equation}$

其中 $\xi \neq \xi_{\varepsilon_1} := \frac{1}{\varepsilon_1} \ln \frac{U_{10}}{M_1}$.

$\xi > \xi_1$, 则 $\underline{U}_1(\xi) = 0$, 即(3.3)成立. 若 $\xi < \xi_1$, 则 $\underline{U}_1(\xi) = U_{10} - M_1 \mathrm{e}^{\varepsilon_1 \xi}$, 从而

$ \begin{align*} & c\underline{U}_1'(\xi) - d_1\left( \mathcal{J} * \underline{U}_1(\xi) - \underline{U}_1(\xi) \right) - \Lambda + \beta_1 \underline{U}_1(\xi)\int_0^\tau K(s)\overline{U}_3(\xi - cs) \mathrm{d}s + (\alpha + \mu_1)\underline{U}_1(\xi) \\ &\leq -c\varepsilon_1 M_1 \mathrm{e}^{\varepsilon_1 \xi} + d_1 M_1 \mathrm{e}^{\varepsilon_1 \xi} \int_{\mathbb{R}} \mathcal{J}(y)\mathrm{e}^{-\varepsilon_1 y} \mathrm{d}y - d_1 M_1 \mathrm{e}^{\varepsilon_1 \xi} - \Lambda + (\alpha + \mu_1)\left( U_{10} - M_1 \mathrm{e}^{\varepsilon_1 \xi} \right) \\ &\quad + \beta_1 \left( U_{10} - M_1 \mathrm{e}^{\varepsilon_1 \xi} \right)\int_0^\tau K(s)\mathrm{e}^{\lambda_c(\xi - cs)} \mathrm{d}s \\ &= \mathrm{e}^{\varepsilon_1 \xi} \left[ -c\varepsilon_1 M_1 + \left(d_1 \int_{\mathbb{R}} \mathcal{J}(y)\mathrm{e}^{-\varepsilon_1 y} \mathrm{d}y - d_1 \right) M_1 - (\alpha + \mu_1)M_1\right. \\ & \left.\quad + \beta_1 U_{10} \mathrm{e}^{(\lambda_c - \varepsilon_1)\xi} \int_0^\tau K(s)\mathrm{e}^{-\lambda_c cs} \mathrm{d}s \right] - \beta_1 M_1 \mathrm{e}^{(\lambda_c + \varepsilon_1)\xi} \int_0^\tau K(s)\mathrm{e}^{-\lambda_c cs} \mathrm{d}s \\ &\leq \mathrm{e}^{\varepsilon_1 \xi} \left[ -c\varepsilon_1 M_1 + \left(d_1 \int_{\mathbb{R}} \mathcal{J}(y)\mathrm{e}^{-\varepsilon_1 y} \mathrm{d}y - d_1 \right) M_1 - (\alpha + \mu_1)M_1 + \beta_1 U_{10} \mathrm{e}^{(\lambda_c - \varepsilon_1)\xi} \right] \\ &= \mathrm{e}^{\varepsilon_1 \xi} \left[ M_1 \left( -c\varepsilon_1 + d_1 \int_{\mathbb{R}} \mathcal{J}(y)\mathrm{e}^{-\varepsilon_1 y} \mathrm{d}y - d_1 - \alpha - \mu_1 \right) + \beta_1 U_{10} \mathrm{e}^{(\lambda_c - \varepsilon_1)\xi} \right]. \end{align*} $

结合核函数$\mathcal{J}$ 的紧支集性, 只需取 $M_1 > U_{10}>0$ 充分大且 $\varepsilon_1>0$ 充分小, 则当 $\xi < \xi_1$ 时, 有

$ c \underline{U}_1'(\xi) - d_1 \bigl( \mathcal{J} * \underline{U}_1(\xi) - \underline{U}_1(\xi)\bigr) - \Lambda + \beta_1 \underline{U}_1(\xi) \int_{0}^{\tau} K(s) \overline{U}_3(\xi - cs) \, \mathrm{d}s + (\alpha + \mu_1) \underline{U}_1(\xi) \leq 0. $

证毕.

引理 3.4 若存在充分小的数 $\varepsilon_2$ 满足 $0 < \varepsilon_2 < \varepsilon_1 < \lambda_c$ 和充分大的正数 $M_2$ 满足 $\frac{1}{\varepsilon_2} \ln \frac{U_{20}}{M_2} < \frac{1}{\varepsilon_1} \ln \frac{U_{10}}{M_1}$, 则函数 $\underline{U}_2(\xi) = \max \left\{ U_{20} - M_2 \mathrm{e}^{\varepsilon_2 \xi}, 0 \right\}$ 满足

$\begin{equation} c \underline{U}_2'(\xi) \leq d_2 \bigl(J * \underline{U}_2(\xi) - \underline{U}_2(\xi)\bigr) + \alpha \underline{U}_1(\xi) - \beta_2 \underline{U}_2(\xi) \int_{0}^{\tau} K(s) \overline{U}_3(\xi - cs) \, \mathrm{d}s - (\gamma_1 + \mu_2) \underline{U}_2(\xi), \end{equation}$

其中 $\xi \neq \xi_{\varepsilon_2} := \frac{1}{\varepsilon_2} \ln \frac{U_{20}}{M_2}$.

引理 3.5 若存在充分小的数 $\varepsilon_3$ 满足 $0 < \varepsilon_3 < \min \left\{ \frac{\varepsilon_1}{2}, \frac{\varepsilon_2}{2} \right\}$ 和充分大的正数 $M_3 > \max \left\{ U_{10}, U_{20} \right\}$, 则函数 $\underline{U}_3(\xi) = \max \left\{ \mathrm{e}^{\lambda_c \xi} \left(1 - M_3 \mathrm{e}^{\varepsilon_3 \xi}\right), 0 \right\}$ 满足

$\begin{equation} c \underline{U}_3'(\xi) \leq d_3 \bigl( \mathcal{J} * \underline{U}_3(\xi) - \underline{U}_3(\xi)\bigr) + (\beta_1 \underline{U}_1(\xi) + \beta_2 \underline{U}_2(\xi)) \int_{0}^{\tau} K(s) \underline{U}_3(\xi - cs) \, \mathrm{d}s - (\gamma - \mu_3) \underline{U}_3(\xi), \end{equation}$

其中 $\xi \neq \xi_{\varepsilon_3} := \frac{1}{\varepsilon_3} \ln \frac{1}{M_3}$.

引理 3.4-3.5 的证明类似引理 3.3, 故此省略.

接下来, 为了建立(2.3) 解的存在性, 对任意给定的 $X > \max \left\{ |\xi_{\varepsilon_1}|, |\xi_{\varepsilon_2}|, |\xi_{\varepsilon_3}|, r \right\}$ (这里 $r$$J(\cdot)$ 的支集半径), 定义集合

$\begin{eqnarray*} \Gamma_X = \left\{ \begin{array}{ll} (\phi(\cdot), \varphi(\cdot), \psi(\cdot)) \in C([-X, X], \mathbb{R}^3) \left| \begin{array}{ll} \text{当 } -X \leq \xi \leq X \text{ 时}, \ \underline{U}_1(\xi) \leq \phi(\xi) \leq U_{10}, \\ \text{当 } -X \leq \xi \leq X \text{ 时}, \ \underline{U}_2(\xi) \leq \varphi(\xi) \leq U_{20}, \\ \text{当 } -X \leq \xi \leq X \text{ 时}, \ \underline{U}_3(\xi) \leq \psi(\xi) \leq \overline{U}_3(\xi), \\ \phi(-X) = \underline{U}_1(-X), \ \varphi(-X) = \underline{U}_2(-X), \\ \psi(-X) = \underline{U}_3(-X) \end{array} \right. \end{array} \right\}. \end{eqnarray*}$

对于任意的 $(\phi(\xi), \varphi(\xi), \psi(\xi)) \in \Gamma_X$, 定义

$ \hat{\phi}(\xi) = \begin{cases} \phi(X), & \xi > X, \\ \phi(\xi), & \vert \xi \vert \leq X, \\ \underline{U}_1(\xi), & \xi < -X, \end{cases} \quad \hat{\varphi}(\xi) = \begin{cases} \varphi(X), & \xi > X, \\ \varphi(\xi), & \vert \xi \vert \leq X, \\ \underline{U}_2(\xi), & \xi < -X, \end{cases} \quad \hat{\psi}(\xi) = \begin{cases} \psi(X), & \xi > X, \\ \psi(\xi), & \vert \xi \vert \leq X, \\ \underline{U}_3(\xi), & \xi < -X. \end{cases} $

显然, $\Gamma_X$ 是闭凸集且 $(\hat{\phi}(\xi), \hat{\varphi}(\xi), \hat{\psi}(\xi))$ 满足

$ \underline{U}_1(\xi) \leq \hat{\phi}(\xi) \leq U_{10}, \ \underline{U}_2(\xi) \leq \hat{\varphi}(\xi) \leq U_{20}, \ \underline{U}_3(\xi) \leq \hat{\psi}(\xi) \leq \overline{U}_3(\xi), \ \forall \xi \in \mathbb{R}. $

对于任意的 $\xi \in [-X, X]$, 考虑初值问题

$\begin{equation} \begin{cases} c U_1'(\xi) = d_1 \int_{\mathbb{R}} \mathcal{J}(y) \hat{\phi}(\xi - y) \, \mathrm{d}y + \Lambda - \beta_1 U_1(\xi) \int_{0}^{\tau} K(s) \hat{\psi}(\xi - cs) \, \mathrm{d}s - (d_1 + \mu_1 + \alpha) U_1(\xi), \\ c U_2'(\xi) = d_2 \int_{\mathbb{R}} \mathcal{J}(y) \hat{\varphi}(\xi - y) \, \mathrm{d}y + \alpha {\phi}(\xi) - \beta_2 U_2(\xi) \int_{0}^{\tau} K(s) \hat{\psi}(\xi - cs) \, \mathrm{d}s \\ - (d_2 + \gamma_1 + \mu_2) U_2(\xi), \\ c U_3'(\xi) = d_3 \int_{\mathbb{R}} \mathcal{J}(y) \hat{\psi}(\xi - y) \, \mathrm{d}y + \beta_1 {\phi}(\xi) \int_{0}^{\tau} K(s) \hat{\psi}(\xi - cs) \, \mathrm{d}s + \beta_2 {\varphi}(\xi) \int_{0}^{\tau} K(s) \hat{\psi}(\xi - cs) \, \mathrm{d}s \\ - (d_3 + \gamma + \mu_3) U_3(\xi), \\ U_1(-X) = \underline{U}_1(-X), \ U_2(-X) = \underline{U}_2(-X), \ U_3(-X) = \underline{U}_3(-X). \end{cases} \end{equation}$

由时滞泛函微分方程理论可知, 初值问题(3.6) 存在唯一解 $(U_{1X}(\xi), U_{2X}(\xi), U_{3X}(\xi)) \in C^1([-X, X])$. 对任意的 $(\phi(\xi), \varphi(\xi), \psi(\xi)) \in \Gamma_X$, 定义算子 $\mathbf{A} = (A_1, A_2, A_3)$

$ U_{1X}(\cdot) = A_1(\hat{\phi}(\cdot), \hat{\varphi}(\cdot), \hat{\psi}(\cdot)), \ U_{2X}(\cdot) = A_2(\hat{\phi}(\cdot), \hat{\varphi}(\cdot), \hat{\psi}(\cdot)), \ U_{3X}(\cdot) = A_3(\hat{\phi}(\cdot), \hat{\varphi}(\cdot), \hat{\psi}(\cdot)). $

类似文献[14] 中的引理 2.7 和引理 2.8, 可以证明算子 $\mathbf{A} : \Gamma_X \to \Gamma_X$ 的全连续性 (引理 3.6-3.7).

引理 3.6 算子 $\mathbf{A} = (A_1, A_2, A_3)$$\Gamma_X$ 映到 $\Gamma_X$.

引理 3.7 算子 $\mathbf{A} : \Gamma_X \to \Gamma_X$ 是全连续的.

由于 $\Gamma_X$ 是有界闭凸集, 故利用引理 3.6-3.7 和 Schauder 不动点定理可知算子 $\mathbf{A}$ 存在不动点 (引理 3.8).

引理 3.8 对任意的 $\xi \in [-X, X]$, 存在 $(U_{1X}^*(\xi), U_{2X}^*(\xi), U_{3X}^*(\xi)) \in \Gamma_X$ 使得

$ \mathbf{A}(U_{1X}^*(\xi), U_{2X}^*(\xi), U_{3X}^*(\xi)) = (U_{1X}^*(\xi), U_{2X}^*(\xi), U_{3X}^*(\xi)). $

定义空间

$ C^{1,1}([-X, X]) := \left\{ u \in C^1([-X, X]) \ \bigg|\ u \text{ 和 } u' \text{ 是 Lipschitz 连续的} \right\} $

及其上的范数

$ \| u \|_{C^{1,1}([-X, X])} = \max_{x \in [-X, X]} |u(x)| + \max_{x \in [-X, X]} |u'(x)| + \sup_{\substack{x,y \in [-X, X] \\ x \neq y}} \frac{|u'(x) - u'(y)|}{|x - y|}. $

接下来, 为了得到(2.3)解的存在性, 需要建立解的先验估计.

引理 3.9 (先验估计) 对任意的 $X > \max\{|\xi_1|, |\xi_2|, |\xi_3|, r\}$, 取 $Y < X$, 则存在与 $Y$ 有关的正数 $C(Y)$ 使得

$ \begin{align*} \left\| U_{1X} \right\|_{C^{1,1}([-Y,Y])} \leq C(Y),\ \left\| U_{2X} \right\|_{C^{1,1}([-Y,Y])} \leq C(Y),\ \left\| U_{3X} \right\|_{C^{1,1}([-Y,Y])} \leq C(Y). \end{align*} $

因为 $(U_{1X}^*(\xi), U_{2X}^*(\xi), U_{3X}^*(\xi))$ 是算子 $\mathbf{A}$ 的不动点, 结合(3.6)可知, 对任意的 $\xi \in [-X, X]$, $(U_{1X}^*(\xi), U_{2X}^*(\xi), U_{3X}^*(\xi))$ 满足

$\begin{equation} \begin{cases} cU_{1X}^{*\prime}(\xi) = d_1\displaystyle\int_{\mathbb{R}} \mathcal{J}(y)\hat{U}_{1X}(\xi - y)\mathrm{d}y + \Lambda - \beta_1 U_{1X}^*(\xi)\displaystyle\int_0^\tau K(s)\hat{U}_{3X}(\xi - cs)\mathrm{d}s \\ \qquad\qquad~~ - (d_1 + \mu_1 + \alpha)U_{1X}^*(\xi), \\ cU_{2X}^{*\prime}(\xi) = d_2\displaystyle\int_{\mathbb{R}} \mathcal{J}(y)\hat{U}_{2X}(\xi - y)\mathrm{d}y - \beta_2 U_{2X}^*(\xi)\displaystyle\int_0^\tau K(s)\hat{U}_{3X}(\xi - cs)\mathrm{d}s \\ \qquad\qquad~~ + \alpha U_{1X}^*(\xi) - (d_2 + \gamma_1 + \mu_2)U_{2X}^*(\xi), \\ cU_{3X}^{*\prime}(\xi) = d_3\displaystyle\int_{\mathbb{R}} \mathcal{J}(y)\hat{U}_{3X}(\xi - y)\mathrm{d}y + \beta_1 U_{1X}^*(\xi)\displaystyle\int_0^\tau K(s)\hat{U}_{3X}(\xi - cs)\mathrm{d}s \\ \qquad\qquad~~ + \beta_2 U_{2X}^*(\xi)\displaystyle\int_0^\tau K(s)\hat{U}_{3X}(\xi - cs)\mathrm{d}s - (d_3 + \gamma + \mu_3)U_{3X}^*(\xi), \end{cases} \end{equation}$

其中

$ \begin{align*} \left( \hat{U}_{1X}(\xi), \hat{U}_{2X}(\xi), \hat{U}_{3X}(\xi) \right) = \begin{cases} \left( U_{1X}(X), U_{2X}(X), U_{3X}(X) \right), & \xi > X, \\ \left( U_{1X}^*(\xi), U_{2X}^*(\xi), U_{3X}^*(\xi) \right), & \vert \xi \vert \leq X, \\ \left( \underline{U}_{1X}(\xi), \underline{U}_{2X}(\xi), \underline{U}_{3X}(\xi) \right), & \xi < -X. \end{cases} \end{align*} $

由于 $ Y < X $, 则 $ [-Y, Y] \subset [-X, X] $, 从而由引理 3.7 可知

$ \begin{align*} \displaystyle\max_{\xi \in [-Y,Y]} \left| U_{1X}'(\xi) \right| \leq \displaystyle\max_{\xi \in [-X,X]} \left| U_{1X}'(\xi) \right| \leq M_0. \end{align*} $

另外, 对任意的 $ \xi \in [-Y, Y] $, 有 $ U_{1X}^*(\xi) \leq U_{10} $, $ U_{2X}^*(\xi) \leq U_{20} $$ U_{3X}^*(\xi) \leq \mathrm{e}^{\lambda c Y} $. 不难验证

$\begin{equation} \begin{cases} \left| U_{1X}^{*\prime}(\xi) \right| \leq \dfrac{(2d_1 + \mu_1 + \alpha)U_{10}}{c} + \dfrac{\Lambda}{c} + \dfrac{\beta_1 U_{10}}{c} \mathrm{e}^{\lambda c Y} := C_1(Y), \\ \left| U_{2X}^{*\prime}(\xi) \right| \leq \dfrac{(2d_2 + \mu_2)U_{20}}{c} + \dfrac{\alpha U_{10}}{c} + \dfrac{\beta_2 U_{20}}{c} \mathrm{e}^{\lambda c Y} := C_2(Y), \\ \left| U_{3X}^{*\prime}(\xi) \right| \leq \left( \dfrac{2d_3 + \mu_3}{c} + \dfrac{\beta_1 U_{10}}{c} + \dfrac{\beta_2 U_{20}}{c} \right) \mathrm{e}^{\lambda c Y} := C_3(Y). \end{cases} \end{equation}$

从而

$\begin{equation} \begin{gathered} \big| U_{1X}^{*}(\xi) - U_{1X}^{*}(\eta) \big| \leq C_1(Y) \big| \xi - \eta \big|, \quad \big| U_{2X}^{*}(\xi) - U_{2X}^{*}(\eta) \big| \leq C_2(Y) \big| \xi - \eta \big|, \\ \big| U_{3X}^{*}(\xi) - U_{3X}^{*}(\eta) \big| \leq C_3(Y) \big| \xi - \eta \big|. \end{gathered} \end{equation}$

另一方面, 由(3.7)可知

$\begin{equation} \begin{split} c \left| U_{1X}^{*\prime}(\xi) - U_{1X}^{*\prime}(\eta) \right| &\leq d_1 \int_{\mathbb{R}} \mathcal{J}(y) \left| \hat{U}_{1X}^*(\xi - y) - \hat{U}_{1X}^*(\eta - y) \right| \mathrm{d}y \\ &\quad + \beta_1 U_{10} \int_0^\tau K(s) \left| U_{3X}^*(\xi - cs) - U_{3X}^*(\eta - cs) \right| \mathrm{d}s \\ &\quad + (d_1 + \mu_1 + \alpha) \left| U_{1X}^*(\xi) - U_{1X}^*(\eta) \right|. \end{split} \end{equation}$

注意到

$\begin{equation} \begin{split} & \left| \int_{-X}^{X} \left( \mathcal{J}(\xi - y) - \mathcal{J}(\eta - y) \right) \hat{U}_{1X}^*(y) \mathrm{d}y \right| \\ &= \left| \int_{\xi - X}^{\xi + X} \mathcal{J}(z) \hat{U}_{1X}^*(\xi - z) \mathrm{d}z - \int_{\eta - X}^{\eta + X} \mathcal{J}(z) \hat{U}_{1X}^*(\eta - z) \mathrm{d}z \right| \\ &= \left| \int_{\xi - X}^{\eta - X} \mathcal{J}(z) \hat{U}_{1X}^*(\xi - z) \mathrm{d}z + \int_{\eta - X}^{\eta + X} \mathcal{J}(z) \hat{U}_{1X}^*(\xi - z) \mathrm{d}z \right. \\ &\quad \left. + \int_{\eta + X}^{\xi + X} \mathcal{J}(z) \hat{U}_{1X}^*(\xi - z) \mathrm{d}z - \int_{\eta - X}^{\eta + X} \mathcal{J}(z) \hat{U}_{1X}^*(\eta - z) \mathrm{d}z \right| \\ &\leq \int_{\xi - X}^{\eta - X} \mathcal{J}(z) \left| \hat{U}_{1X}^*(\xi - z) \right| \mathrm{d}z + \int_{\eta + X}^{\xi + X} \mathcal{J}(z) \left| \hat{U}_{1X}^*(\xi - z) \right| \mathrm{d}z \\ &\quad + \int_{\eta - X}^{\eta + X} \mathcal{J}(z) \left| \hat{U}_{1X}^*(\xi - z) - \hat{U}_{1X}^*(\eta - z) \right| \mathrm{d}z \\ &\leq (2 U_{10} \left\| \mathcal{J} \right\|_{L^\infty} + M_0) \left| \xi - \eta \right|. \end{split} \end{equation}$

$ L_J $ 是核函数 $ \mathcal{J}(\cdot) $ 的 Lipschitz 常数, 结合(3.11)和假设条件$(A_{1})~$, 可得

$\begin{matrix} & d_1\biggl| \int_{-\infty}^{+\infty} \mathcal{J}(y)\bigl( \hat{U}_{1X}^*(\xi - y) - \hat{U}_{1X}^*(\eta - y) \bigr) \mathrm{d}y \biggr| \notag \\ &= d_1\biggl| \int_{-\infty}^{+\infty} \bigl( \mathcal{J}(\xi - y) - \mathcal{J}(\eta - y) \bigr) \hat{U}_{1X}^*(y) \mathrm{d}y \biggr| \notag \\ &\leq d_1\int_{-\infty}^{-X} \bigl| \bigl( \mathcal{J}(\xi - y) - \mathcal{J}(\eta - y) \bigr) \underline{U}_{1X}(y) \bigr| \mathrm{d}y + d_1\int_{-X}^{X} \bigl| \bigl( \mathcal{J}(\xi - y) - \mathcal{J}(\eta - y) \bigr) U_{1X}^*(y) \bigr| \mathrm{d}y \notag \\ & + d_1\int_{X}^{+\infty} \bigl| \bigl( \mathcal{J}(\xi - y) - \mathcal{J}(\eta - y) \bigr) U_{1X}(X) \bigr| \mathrm{d}y \notag \\ &\leq d_1\int_{-\infty}^{-X} \bigl| \bigl( \mathcal{J}(\xi - y) - \mathcal{J}(\eta - y) \bigr) \bigl( U_{10} - M_1 \mathrm{e}^{\varepsilon_1 y} \bigr) \bigr| \mathrm{d}y + d_1 (2 U_{10} \| \mathcal{J} \|_{L^\infty} + M_0) |\xi - \eta| \notag \\ & + d_1\int_{X}^{+\infty} \bigl| \bigl( \mathcal{J}(\xi - y) - \mathcal{J}(\eta - y) \bigr) U_{1X}(X) \bigr| \mathrm{d}y \notag \\ &\leq d_1 U_{10} \int_{\xi + X}^{\eta + X} |\mathcal{J}(z)| \mathrm{d}z + d_1 U_{10} \int_{\eta - X}^{\xi - X} |\mathcal{J}(z)| \mathrm{d}z + M_1 d_1\int_{-\infty}^{-X} \bigl| \mathcal{J}(\xi - y) - \mathcal{J}(\eta - y) \bigr| \mathrm{e}^{\varepsilon_1 y} \mathrm{d}y \notag \\ & + d_1 (2 U_{10} \| \mathcal{J} \|_{L^\infty} + M_0) |\xi - \eta| \notag \\ &\leq 2 d_1 U_{10} \| \mathcal{J} \|_{L^\infty} |\xi - \eta| + \frac{1}{\varepsilon_1} M_1 d_1 L_J |\xi - \eta| \mathrm{e}^{-\varepsilon_1 X} + d_1 (2 U_{10} \| \mathcal{J} \|_{L^\infty} + M_0) |\xi - \eta| \notag \\ &= d_1 \bigl( M_1^2 L_J \mathrm{e}^{-\varepsilon_1 X} + 4 U_{10} \| \mathcal{J} \|_{L^\infty} + M_0 \bigr) |\xi - \eta|. \end{matrix}$

由(3.10)和(3.12)可知

$\begin{equation} \left| U_{1X}^{*\prime}(\xi) - U_{1X}^{*\prime}(\eta) \right| \leq C_{U_1} \left| \xi - \eta \right|, \end{equation}$

其中,

$\begin{equation} C_{U_1} = \frac{1}{c} \Bigl( d_1 \bigl( M_1^2 L_J \mathrm{e}^{-\varepsilon_1 X} + 4 U_{10} \| \mathcal{J} \|_{L^\infty} + 2 M_0 \bigr) + \beta_1 U_{10} C_3(Y) + (d_1 + \mu_1 + \alpha) C_1(Y) \Bigr), \end{equation}$

进而 $ \| U_{1X}(\cdot) \|_{C^{1,1}([-Y,Y])} \leq C(Y) $. 同理 $ \| U_{2X}(\cdot) \|_{C^{1,1}([-Y,Y])} \leq C(Y) $$ \| U_{3X}(\cdot) \|_{C^{1,1}([-Y,Y])} \leq C(Y) $. 证毕.

对任意的 $ n \in \mathbb{N} $, 取单调递增序列 $ \{ X_n \}_{n=1}^\infty $ 满足 $ X_n \geq \max\{ -\xi_1, -\xi_2, -\xi_3 \} $, 且对任意的 $ n \in \mathbb{N} $, 有 $ X_n > Y + r $$ \lim\limits_{n \to \infty} X_n = +\infty $, 其中 $ r $$ \mathcal{J}(\cdot) $ 的支集半径, 则对每一个 $ c > c^* $, 存在 $ (U_{1X_n}, U_{2X_n}, U_{3X_n}) \in \Gamma_{X_n} $ 满足引理 3.9 和(3.7), 故对序列 $ \{ (U_{1X_n}, U_{2X_n}, U_{3X_n}) \} $, 可抽取子列 $ \{ U_{1X_{n_k}} \}_{k \in \mathbb{N}} $, $ \{ U_{2X_{n_k}} \}_{k \in \mathbb{N}} $, $ \{ U_{3X_{n_k}} \}_{k \in \mathbb{N}} $, 使得当 $ k \to +\infty $ 时, 这些子列在 $ C^1(\mathbb{R}) $ 拓扑意义下收敛到函数 $ (U_1, U_2, U_3) \in C^1(\mathbb{R}) $, 即 $ U_{1X_{n_k}} \to U_1 $, $ U_{2X_{n_k}} \to U_2 $, $ U_{3X_{n_k}} \to U_3 $. 利用 $ \mathcal{J}(\cdot) $ 的紧性和控制收敛定理可得

$ \begin{align*} \begin{split} \lim_{k \to \infty} \int_{\mathbb{R}} \mathcal{J}(y) \hat{U}_{1X_{n_k}}(\xi - y) \mathrm{d}y &= \int_{\mathbb{R}} \mathcal{J}(y) U_1(\xi - y) \mathrm{d}y = \mathcal{J} * U_1(\xi), \\ \lim_{k \to \infty} \int_{\mathbb{R}} \mathcal{J}(y) \hat{U}_{2X_{n_k}}(\xi - y) \mathrm{d}y &= \int_{\mathbb{R}} \mathcal{J}(y) U_2(\xi - y) \mathrm{d}y = \mathcal{J} * U_2(\xi), \end{split} \end{align*} $

以及

$ \begin{align*} \lim_{k \to \infty} \int_{\mathbb{R}} \mathcal{J}(y) \hat{U}_{3X_{n_k}}(\xi - y) \mathrm{d}y = \int_{\mathbb{R}} \mathcal{J}(y) U_3(\xi - y) \mathrm{d}y = \mathcal{J} * U_3(\xi). \end{align*} $

因此, $ (U_1, U_2, U_3) $ 满足(2.3)及不等式

$ \begin{align*} \underline{U}_1(\xi) \leq U_1(\xi) \leq U_{10}, \ \underline{U}_2(\xi) \leq U_2(\xi) \leq U_{20}, \ \underline{U}_3(\xi) \leq U_3(\xi) \leq \mathrm{e}^{\lambda c \xi}. \end{align*} $

为了得到 $ U_3(\xi) $$ \mathbb{R} $ 上的有界性 (引理 3.13), 还需建立如下结论 (引理 3.10-3.12).

引理 3.10 存在正常数 $ C > 0 $, 使得对任意的 $ \xi \in \mathbb{R} $, 有

$ \begin{align*} \int_{\mathbb{R}} \mathcal{J}(y) \frac{U_3(\xi - y)}{U_3(\xi)} \mathrm{d}y < C, \int_0^\tau K(s) \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s < C, \left| \frac{U_3'(\xi)}{U_3(\xi)} \right| < C. \end{align*} $

首先证明 $ \int_{\mathbb{R}} \mathcal{J}(y) \frac{U_3(\xi - y)}{U_3(\xi)} \mathrm{d}y < +\infty $.$ \theta(\xi) = \frac{U_3'(\xi)}{U_3(\xi)} $, $ \rho = \frac{d_3}{c} $$ \omega = \frac{d_3 + r + \mu_3}{c} $, 由(2.3)的第三个式子可得

$\begin{equation} \begin{split} \theta(\xi) &= \frac{d_3}{c} \int_{\mathbb{R}} \mathcal{J}(y) \frac{U_3(\xi - y)}{U_3(\xi)} \mathrm{d}y - \omega + \frac{\beta_1}{c} U_1(\xi) \int_0^\tau K(s) \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s\\ &\quad + \frac{\beta_2}{c} U_2(\xi) \int_0^\tau K(s) \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s. \end{split} \end{equation}$

$ W(\xi) = \mathrm{e}^{\omega \xi + \int_0^\xi \theta(s) \mathrm{d}s} $, 则

$\begin{equation} W'(\xi) = (\omega + \theta(\xi)) W(\xi) \geq \rho \int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{\int_\xi^{\xi - y} \theta(s) \mathrm{d}s} \mathrm{d}y W(\xi) \geq 0. \end{equation}$

另外,

$\begin{equation} \mathrm{e}^{\int_\xi^{\xi - y} \theta(s) \mathrm{d}s} = \mathrm{e}^{\int_\xi^{\xi - y} \frac{U_3'(t)}{U_3(t)} \mathrm{d}t} = \mathrm{e}^{\int_\xi^{\xi - y} \frac{1}{U_3(t)} \mathrm{d}U_3(t)} = \mathrm{e}^{\ln U_3(t) \big|_\xi^{\xi - y}} = \frac{U_3(\xi - y)}{U_3(\xi)}. \end{equation}$

因此, $ W(\xi) $$ \xi \in \mathbb{R} $ 上非减. 取定常数 $ r_0 > 0 $ 使得 $ 2r_0 < r $ (其中 $ r $$ \mathcal{J}(\cdot) $ 的支集半径), 对(3.16)式两边从 $ -\infty $$ \xi $ 积分, 并结合(3.17)可得

$ \begin{align*} \begin{split} W(\xi) &\geq \rho \int_{-\infty}^{\xi} \int_{-\infty}^{+\infty} \mathcal{J}(y) \mathrm{e}^{\int_{x}^{x - y} \theta(s) \mathrm{d}s} \mathrm{d}y W(x) \mathrm{d}x \\ &= \rho \int_{-\infty}^{\xi} \int_{-\infty}^{+\infty} \mathcal{J}(y) \frac{U_3(x - y)}{U_3(x)} W(x) \mathrm{d}y\mathrm{d}x \\ &= \rho \int_{-\infty}^{+\infty} \mathcal{J}(y) \mathrm{e}^{\omega y} \int_{-\infty}^{\xi} W(x - y) \mathrm{d}x\mathrm{d}y \\ & \geq \rho \int_{-\infty}^{+\infty} \mathcal{J}(y) \mathrm{e}^{\omega y} \int_{\xi - r_0}^{\xi} W(x - y) \mathrm{d}x\mathrm{d}y \\ & \geq \rho r_0 \int_{-\infty}^{+\infty} \mathcal{J}(y) \mathrm{e}^{\omega y} W(\xi - r_0 - y) \mathrm{d}y. \end{split} \end{align*} $

类似地, 对(3.16)两边从 $ \xi - r_0 $$ \xi $ 积分, 并结合 $ W(\xi) $ 的非减性可得

$ \begin{align*} \begin{split} W(\xi) - W(\xi - r_0) &\geq \rho \int_{\xi - r_0}^{\xi} \int_{-\infty}^{+\infty} \mathcal{J}(y) \mathrm{e}^{\int_{x}^{x - y} \theta(s) \mathrm{d}s} \mathrm{d}y W(x) \mathrm{d}x \\ &= \rho \int_{\xi - r_0}^{\xi} \int_{-\infty}^{+\infty} \mathcal{J}(y) \frac{U_3(x - y)}{U_3(x)} W(x) \mathrm{d}y\mathrm{d}x \\ &= \rho \int_{-\infty}^{+\infty} \mathcal{J}(y) \mathrm{e}^{\omega y} \int_{\xi - r_0}^{\xi} W(x - y) \mathrm{d}x\mathrm{d}y \\ &\geq \rho r_0 \int_{-\infty}^{-2 r_0} \mathcal{J}(y) \mathrm{e}^{\omega y} W(\xi - r_0 - y) \mathrm{d}y \\ &\geq \rho r_0 \int_{-\infty}^{-2 r_0} \mathcal{J}(y) \mathrm{e}^{\omega y} \mathrm{d}y W(\xi + r_0), \end{split} \end{align*} $

所以 $ W(\xi) \geq \rho r_0 \int_{-\infty}^{-2 r_0} \mathcal{J}(y) \mathrm{e}^{\omega y} \mathrm{d}y W(\xi + r_0) $.$ W(\xi) $ 的定义式, 通过计算不难得出

$\begin{equation} \int_{\mathbb{R}} \mathcal{J}(y) \frac{U_3(\xi - y)}{U_3(\xi)} \mathrm{d}y = \int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{\omega y} \frac{W(\xi - y)}{W(\xi)} \mathrm{d}y. \end{equation}$

因此, 对任意的 $ \xi \in \mathbb{R} $, 有

$\begin{equation} \max\left\{ \int_{-\infty}^0 \mathcal{J}(y) \mathrm{e}^{\omega y} \frac{W(\xi - r_0 - y)}{W(\xi)} \mathrm{d}y, \int_0^{+\infty} \mathcal{J}(y) \mathrm{e}^{\omega y} \frac{W(\xi - r_0 - y)}{W(\xi)} \mathrm{d}y \right\} \leq \frac{1}{\rho r_0}, \end{equation}$

$\begin{equation} W(\xi + r_0) \leq \sigma_0 W(\xi), \end{equation}$

其中 $ \sigma_0 = \frac{1}{\rho r_0 \int_{-\infty}^{-2 r_0} \mathcal{J}(y) \mathrm{e}^{\omega y} \mathrm{d}y} $, 由 $ 2r_0 < r $ 可知 $ \sigma_0 $ 的分母不为零, 从而 $ \sigma_0 $ 有意义. 结合 $ W(\xi) $ 的非减性以及条件 $ (A_1) $, (3.19)和(3.20)可知, 对任意的 $ \xi \in \mathbb{R} $, 有

$\begin{equation} \begin{split} & \int_{\mathbb{R}} \mathcal{J}(y) \frac{U_3(\xi - y)}{U_3(\xi)} \mathrm{d}y \\ &= \int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{\omega y} \frac{W(\xi - y)}{W(\xi)} \mathrm{d}y \\ &= \int_{-\infty}^0 \mathcal{J}(y) \mathrm{e}^{\omega y} \frac{W(\xi - y)}{W(\xi)} \mathrm{d}y + \int_0^{+\infty} \mathcal{J}(y) \mathrm{e}^{\omega y} \frac{W(\xi - y)}{W(\xi)} \mathrm{d}y \\ &\leq \sigma_0 \int_{-\infty}^0 \mathcal{J}(y) \mathrm{e}^{\omega y} \frac{W(\xi - r_0- y)}{W(\xi)} \mathrm{d}y + \sigma_0 \int_0^{+\infty} \mathcal{J}(y) \mathrm{e}^{\omega y} \frac{W(\xi - r_0- y)}{W(\xi)} \mathrm{d}y \\ &\leq \frac{2 \sigma_0}{\rho r_0} := C_1. \end{split} \end{equation}$

下面证明 $ \int_0^\tau K(s) \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s < +\infty $.$ \tilde{\rho} = \frac{\beta}{c} $, 其中 $ \beta = \max\{\beta_1, \beta_2\} $. 由(3.16)可知, 对任意的 $ \xi \in \mathbb{R} $, 有

$\begin{equation} W'(\xi) \geq \tilde{\rho} \int_0^\tau K(s) \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s W(\xi) = \tilde{\rho} \int_0^\tau K(s) \mathrm{e}^{\int_\xi^{\xi - cs} \theta(t) \mathrm{d}t} \mathrm{d}s W(\xi). \end{equation}$

对(3.22)两边从 $ -\infty $$ \xi $ 积分, 有

$ \begin{align*} \begin{split} W(\xi) &\geq \tilde{\rho} \int_{-\infty}^{\xi} \int_0^\tau K(s) \frac{U_3(\xi - cs)}{U_3(\xi)} W(x) \mathrm{d}s \mathrm{d}x \\ &= \tilde{\rho} \int_{-\infty}^{\xi} \int_0^\tau K(s) \mathrm{e}^{\omega cs} W(x - cs) \mathrm{d}x \mathrm{d}s \\ &\geq \tilde{\rho} \int_0^\tau K(s) \mathrm{e}^{\omega cs} \int_{\xi - r_0}^{\xi} W(x - cs) \mathrm{d}x \mathrm{d}s \\ &\geq \tilde{\rho} r_0 \int_0^\tau K(s) \mathrm{e}^{\omega cs} W(\xi - r_0 - cs) \mathrm{d}s. \end{split} \end{align*} $

因为对任意的 $ \xi \in \mathbb{R} $, 有 $ W(\xi + r_0) \leq \sigma_0 W(\xi) $, 从而,

$ \begin{align*} W(\xi) \geq \tilde{\rho} r_0 \int_0^\tau K(s) \mathrm{e}^{\omega cs} W(\xi - r_0 - cs) \mathrm{d}s \geq \frac{\tilde{\rho} r_0}{\sigma_0} \int_0^\tau K(s) \mathrm{e}^{\omega cs} W(\xi - cs) \mathrm{d}s. \end{align*} $

$\begin{equation} \int_0^\tau K(s) \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s = \int_0^\tau K(s) \mathrm{e}^{\omega cs} \frac{W(\xi - cs)}{W(\xi)} \mathrm{d}s \leq \frac{\sigma_0}{\tilde{\rho} r_0} := C_2. \end{equation}$

此外, 结合(3.15),(3.21) 和(3.23) 可知

$ \begin{split} |\theta(\xi)| = \left| \frac{U_3'(\xi)}{U_3(\xi)} \right| &\leq \frac{d_3}{c} \int_{\mathbb{R}} \mathcal{J}(y) \frac{U_3(\xi - y)}{U_3(\xi)} \mathrm{d}y + \omega + \frac{\beta_1}{c} U_1(\xi) \int_0^\tau K(s) \frac{U_3(\xi - y)}{U_3(\xi)} \mathrm{d}s \\ & \quad + \frac{\beta_2}{c} U_2(\xi) \int_0^\tau K(s) \frac{U_3(\xi - y)}{U_3(\xi)} \mathrm{d}s \\ &\leq \rho C_1 + \omega + (U_{10} + U_{20}) \tilde{\rho} C_2 =: C_3. \end{split} $

由此可得

$ \int_{\mathbb{R}} \mathcal{J}(y) \frac{U_3(\xi - y)}{U_3(\xi)} \mathrm{d}y < C, \int_0^\tau K(s) \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s < C, \left| \frac{U_3'(\xi)}{U_3(\xi)} \right| < C,$

其中 $ C = \max\{C_1, C_2, C_3\} $. 证毕.

引理 3.1 选取 $ c_k \in (c^*, c^* + 1) $, 并且 $ \{ c_k, U_{1k}, U_{2k}, U_{3k} \} $ ($ k \in \mathbb{N} $) 是(2.3)的解序列, 其波速为 $ \{ c_k \} $. 若存在序列 $ \{ \xi_k \} $, 使得当 $ k \to +\infty $ 时, $ U_{3k}(\xi_k) \to +\infty $, 则当 $ k \to +\infty $ 时, $ U_{1k}(\xi_k) \to 0 $$ U_{2k}(\xi_k) \to 0 $.

先证当 $ k \to +\infty $ 时, $ U_{1k}(\xi_k) \to 0 $. 利用反证法, 假设 $ \{ \xi_k \}_{k \in \mathbb{N}} $ 存在子序列, 仍记为 $ \{ \xi_k \} $, 使得当 $ k \to +\infty $$ U_{3k}(\xi_k) \to +\infty $, 并且对任意的 $ k \in \mathbb{N} $ 以及正常数 $ \varpi > 0 $, 有 $ U_{1k}(\xi_k) \geq \varpi $. 由(2.3)的第一个方程可知 $ U_{1k}'(\xi) \leq \frac{2d_1 U_{10} + \Lambda}{c^*} := \eta_0 $, $ \eta_0 > 0 $.

$ \eta = \frac{\varpi}{\eta_0} $, 则对任意的 $ \xi \in [\xi_k - \eta, \xi_k] $, 有 $ U_{1k}(\xi) \geq \frac{\varpi}{2} $, 其中 $ k \in \mathbb{N} $. 由引理 3.10 可知, 存在正数 $ C_0 > 0 $ 使得 $ \left| \frac{U_{3k}'}{U_{3k}} \right| < C_0 $. 从而, 对任意的 $ \xi \in [\xi_k - \eta, \xi_k] $, 有

$ \begin{align*} \int_0^\tau K(s) \frac{U_{3k}(\xi_k)}{U_{3k}(\xi - cs)} \mathrm{d}s = \int_0^\tau K(s) \mathrm{e}^{\int_{\xi - cs}^{\xi_k} \frac{U_{3k}'(t)}{U_{3k}(t)} \mathrm{d}t} \mathrm{d}s \leq \int_0^\tau K(s) \mathrm{e}^{C_0 (cs + \eta)} \mathrm{d}s, \end{align*} $

$\min_{\xi \in [\xi_k - \eta, \xi_k]} \int_0^\tau K(s) U_{3k}(\xi - cs) \mathrm{d}s \geq \frac{1}{\int_0^\tau K(s) \mathrm{e}^{C_0 (cs + \eta)} \mathrm{d}s} U_{3k}(\xi_k). $

因为当 $ k \to +\infty $ 时, $ U_{3k}(\xi_k) \to +\infty $, 所以

$ \min_{\xi \in [\xi_k - \eta, \xi_k]} \int_0^\tau K(s) U_{3k}(\xi - cs) \mathrm{d}s \to +\infty (k \to +\infty). $

由(2.3)的第一个方程可知, 当 $ k \to +\infty $ 时, 有

$ \begin{align*} \max_{\xi \in [\xi_k - \eta, \xi_k]} U_{1k}'(\xi) \leq \eta_0 - \frac{\beta_1 \varpi}{2(c^* + 1)} \min_{\xi \in [\xi_k - \eta, \xi_k]} \int_0^\tau K(s) U_{3k}(\xi - cs) \mathrm{d}s \to -\infty. \end{align*} $

故存在 $ K > 0 (K \in \mathbb{N}) $, 使得对任意的 $ k \geq K $, 有

$\begin{equation} U_{1k}'(\xi) \leq -\frac{2U_{10}}{\eta}, \ \xi \in [\xi_k - \eta, \xi_k]. \end{equation}$

因为对任意的 $ k \in \mathbb{N} $, 有 $ U_{1k} \leq U_{10} $, 则由(3.24)可知 $ U_{1k}'(\xi_k) \leq -U_{10} < 0 $, 与 $ U_{1k}(\xi_k) \geq \varpi $ 矛盾, 因此 $ U_{1k}(\xi_k) \to 0 (k \to +\infty) $. 同理可证 $ U_{2k}(\xi_k) \to 0 (k \to +\infty) $. 证毕.

引理 3.12$ \limsup\limits_{\xi \to +\infty} U_3(\xi) = +\infty $, 则 $ \lim\limits_{\xi \to +\infty} U_3(\xi) = +\infty $.

反设结论不成立, 即 $ \liminf\limits_{\xi \to +\infty} U_3(\xi) := U_{3\inf} < +\infty $, 则存在序列 $ \{ \xi_k \} $ 使得当 $ k \to +\infty $$ \xi_k \to +\infty $ 时, 有 $ \lim\limits_{k \to +\infty} U_3(\xi_k) = U_{3\inf} $. 不失一般性, 取 $ \varepsilon = 1 $, 则存在 $ \mathbb{N} $, 使得当 $ k > \mathbb{N} $ 时, 有 $ U_3(\xi_k) < U_{3\inf} + 1 $.

对任意的 $ k \in \mathbb{N} $, 取 $ \eta_k \in [\xi_k, \xi_{k+1}] $ 使得 $ U_3(\eta_k) = \max\limits_{\xi \in [\xi_k, \xi_{k+1}]} U_3(\xi) $. 由于 $ \limsup\limits_{\xi \to +\infty} U_3(\xi) = +\infty $, 则当 $ k \to +\infty $ 时, 有 $ \limsup\limits_{k \to +\infty} U_3(\eta_k) = +\infty $.$ m_0 = \sup\limits_{\xi \in \mathbb{R}} \left| \frac{U_3'(\xi)}{U_3(\xi)} \right| $, 假设 $ U_3(\eta_k) \geq (U_{3\inf} + 1) \mathrm{e}^{m_0 r} $, 其中 $ r $$ J(\cdot) $ 的支集半径. 注意到, 当 $ |\xi - \eta_k| \leq r $ 时, 有

$ \frac{U_3(\eta_k)}{U_3(\xi)} = \mathrm{e}^{\int_\xi^{\eta_k} \frac{U_3'(t)}{U_3(t)} \mathrm{d}t} \leq \mathrm{e}^{m_0 |\eta_k - \xi|} \leq \mathrm{e}^{m_0 r}. $

则对所有的 $ \xi \in [\eta_k - r, \eta_k + r] $, 有 $ U_3(\xi) \geq U_{3\inf} + 1 $. 故不难得到 $ [\eta_k - r, \eta_k + r] \subset (\xi_k, \xi_{k+1}) $. 由(2.3)的第三个方程可知,

$\begin{equation} \begin{split} 0 = c U_3'(\eta_k) &= d_3 \int_{\mathbb{R}} \mathcal{J}(y) \big( U_3(\eta_k - y) - U_3(\eta_k) \big) \mathrm{d}y + \beta_1 U_1(\eta_k) \int_0^\tau K(s) U_3(\eta_k - cs) \mathrm{d}s \\ &\quad + \beta_2 U_2(\eta_k) \int_0^\tau K(s) U_3(\eta_k - cs) \mathrm{d}s - (\gamma + \mu_3) U_3(\eta_k). \end{split} \end{equation}$

此外, 由引理 3.11 可知, 当 $ \limsup\limits_{\xi \to +\infty} U_3(\eta_k) = +\infty \ (k \to +\infty) $ 时, $ U_1(\eta_k) \to 0, U_2(\eta_k) \to 0 $. 因此, 由(3.25)可知 $ 0 \leq -(\gamma + \mu_3) U_3(\eta_k) < 0 $, 这出现了矛盾. 故假设不成立, 即 $ \lim\limits_{\xi \to +\infty} U_3(\xi) = +\infty $. 证毕.

进一步, 为了证明 $ U_3(\xi) $$ \mathbb{R} $ 上的有界性, 还需用到文献[17]中的命题 3.1.

命题 3.1[17] 假设 $c > 0$, 且 $B(\cdot)$ 是连续函数, 满足 $B(\pm\infty) := \lim\limits_{\xi \to \pm\infty} B(\xi)$ 存在. 假设 $Z(\xi)$ 满足方程

$ cZ(\xi) = \int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{\int_{\xi}^{\xi - y} Z(s) \mathrm{d}s} \mathrm{d}y + B(\xi), \quad \xi \in \mathbb{R}, $

$Z$$\mathbb{R}$ 上一致连续且有界. 此外, 极限 $\mu^{\pm} := \lim\limits_{\xi \to \pm\infty} Z(\xi)$ 存在, 且是特征方程

$ c\mu = \int_{\mathbb{R}} \mathcal{J}_i(y) \mathrm{e}^{-\mu y} \mathrm{d}y + B(\pm\infty), \ (i = 1,2,3) $

的实根.

引理 3.13$U_3(\xi)$$\mathbb{R}$ 上有界.

利用反证法. 假设 $\limsup\limits_{\xi \to +\infty} U_3(\xi) = +\infty$, 则由引理 3.12 可知 $\lim\limits_{\xi \to +\infty} U_3(\xi) = +\infty$, 从而, 结合引理 3.11, 有

$\begin{equation} \lim\limits_{\xi \to +\infty} U_1(\xi) = 0, \ \lim\limits_{\xi \to +\infty} U_2(\xi) = 0. \end{equation}$

$\theta(\xi) = \dfrac{U_3'(\xi)}{U_3(\xi)}$, 由(2.3)的第三个方程可得

$\begin{equation} \begin{split} c\theta(\xi) &= d_3\int_{\mathbb{R}} \mathcal{J}(y) \dfrac{U_3(\xi - y)}{U_3(\xi)} \mathrm{d}y - d_3 + \beta_1 U_1(\xi)\int_{0}^{\tau} K(s) \dfrac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s \\ &\quad + \beta_2 U_2(\xi)\int_{0}^{\tau} K(s) \dfrac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s - (\gamma + \mu_3) \\ &= d_3\int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{\int_{\xi}^{\xi - y} \theta(s) \mathrm{d}s} \mathrm{d}y - d_3 + \beta_1 U_1(\xi)\int_{0}^{\tau} K(s) \dfrac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s \\ &\quad + \beta_2 U_2(\xi)\int_{0}^{\tau} K(s) \dfrac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s - (\gamma + \mu_3), \end{split} \end{equation}$

由引理 3.10 可知存在 $C > 0$ 使得 $\int_{0}^{\tau} K(s) \frac{U_{3}(\xi - cs)}{U_{3}(\xi)} \mathrm{d}s < C$, 结合 $\lim\limits_{\xi \to +\infty} (U_{1}(\xi), U_{2}(\xi)) = (0, 0)$, $\lim\limits_{\xi \to -\infty} (U_{1}(\xi), U_{2}(\xi)) = (U_{10}, U_{20})$ 和命题 3.1 可知 $\lim\limits_{\xi \to +\infty} \theta(\xi) = \lambda$ 存在, 且满足

$\begin{equation} d_{3} \left( \int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{-\lambda y} \mathrm{d}y - 1 \right) - c\lambda - (\gamma + \mu_{3}) = 0. \end{equation}$

$f(\lambda, c) := d_{3} \left( \int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{-\lambda y} \mathrm{d}y - 1 \right) - c\lambda - (\gamma + \mu_{3})$, 计算可知 $f(0, c) < 0$, $\left. \frac{\partial f(\lambda, c)}{\partial \lambda} \right|_{\lambda = 0} < 0$, $\frac{\partial^{2} f(\lambda, c)}{\partial \lambda^{2}} > 0$$\lim\limits_{\lambda \to \infty} f(\lambda, c) = +\infty$. 因此, (3.28) 有唯一正实根 $\lambda_{0}$. 因为 $U_{3}(\xi) > 0$$\lim\limits_{\xi \to +\infty} U_{3}(\xi) = +\infty$, 则由反证法不难得到 $\lim\limits_{\xi \to +\infty} \theta(\xi) = \lambda \geq 0$, 故 $\lim\limits_{\xi \to +\infty} \theta(\xi) = \lambda_{0}$.

另一方面, 由引理 2.1 和引理 3.1 可知, 当 $c > c^{*}$ 时, 对任意的 $\xi \in \mathbb{R}$, 有 $U_{3}(\xi) \leq \mathrm{e}^{\lambda_{c} \xi}$, 其中 $0 < \lambda_{c} (\leq \lambda_{2})$ 是方程

$\begin{equation} d_3\left( \int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{-\lambda y} \mathrm{d}y - 1 \right) - c\lambda + \beta_1 U_{10} + \beta_2 U_{20} - (\gamma + \mu_3) = 0 \end{equation}$

的较小正实根, $\lambda_2$ 是较大正实根. 注意到,

$ d_3\left( \int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{-\lambda_2 y} \mathrm{d}y - 1 \right) - c\lambda_2 - (\gamma + \mu_3) = -\beta_1 U_{10} - \beta_2 U_{20} < 0, $

通过简单分析, 不难得到 $\lambda_2 < \lambda_0$.$\lim\limits_{\xi \to +\infty} \theta(\xi) = \lambda_0$ 可知, 存在充分大的 $\xi_* > 0$ 使得对任意的 $\xi \geq \xi_*$, 有

$ \ln \frac{U_3(\xi)}{U_3(\xi_*)} = \ln U_3(\xi) - \ln U_3(\xi_*) = \int_{\xi_*}^{\xi} \theta(s) \mathrm{d}s \geq \int_{\xi_*}^{\xi} \frac{\lambda_2 + \lambda_0}{2} \mathrm{d}s = \frac{\lambda_2 + \lambda_0}{2} (\xi - \xi_*), $

从而,

$ \frac{U_3(\xi)}{U_3(\xi_*)} \geq \mathrm{e}^{\frac{\lambda_2 + \lambda_0}{2} (\xi - \xi_*)} = \mathrm{e}^{\frac{\lambda_2 + \lambda_0}{2} \xi} \mathrm{e}^{-\frac{\lambda_2 + \lambda_0}{2} \xi_*}. $

$\widetilde{C} = \mathrm{e}^{-\frac{\lambda_2 + \lambda_0}{2} \xi_*} U_3(\xi_*)$, 则 $U_3(\xi) \geq \widetilde{C} \mathrm{e}^{\frac{\lambda_2 + \lambda_0}{2} \xi}$, 又因为 $U_3(\xi) \leq \mathrm{e}^{\lambda_c \xi}$, 而 $\lambda_c < \frac{\lambda_2 + \lambda_0}{2}$, 这出现了矛盾. 因此 $U_3$ 有界. 证毕.

由于 $U_3(\cdot)$ 有界, 则存在正常数 $\rho > 0$ 使得 $U_3(\xi) < \rho$.此外, 不难验证 $\dfrac{\Lambda}{\mu_1 + \alpha + \beta_1 \rho}$$\dfrac{\alpha\Lambda}{(\mu_1 + \alpha + \beta_1 \rho)(\gamma_1 + \mu_2 + \beta_2 \rho)}$ 分别是 $U_1(\cdot)$$U_2(\cdot)$ 的下解, 类似文献[14] 中的命题 2.1 可得如下结论.

引理 3.14 对任意的 $\xi \in \mathbb{R}$, $U_1(\xi), U_2(\xi)$$U_3(\xi)$ 满足

$ \frac{\Lambda}{\mu_1 + \alpha + \beta_1 \rho} \leq U_1(\xi) \leq U_{10}, \frac{\alpha \Lambda}{(\mu_1 + \alpha + \beta_1 \rho)(\gamma_1 + \mu_2 + \beta_2 \rho)} \leq U_2(\xi) \leq U_{20}, \underline{U_3}(\xi) \leq U_3(\xi) \leq \rho. $

引理 3.15$R_0 > 1$ 时, 对任意的 $c > c^*$, 有 $\liminf\limits_{\xi \to +\infty} U_3(\xi) > 0$.

只需证明, 若对充分小的 $\varepsilon_0 > 0$, 存在 $\hat{\xi} \in \mathbb{R}$ 使得 $U_3(\hat{\xi}) \leq \varepsilon_0$, 则对任意的 $\xi \in \mathbb{R}$, 有 $U_3'(\xi) > 0$. 假设不存在这样的 $\varepsilon_0$, 即存在序列 $\{\xi_n\}_{n \in \mathbb{N}}$ 使得当 $n \to +\infty$$U_3(\xi_n) \to 0$ 时, 有 $U_3'(\xi_n) \leq 0$. 定义

$ U_{1n}(\xi) := U_1(\xi_n + \xi), \quad U_{2n}(\xi) := U_2(\xi_n + \xi), \quad U_{3n}(\xi) := U_3(\xi_n + \xi), $

故当 $n \to +\infty$ 时, $U_{3n}(0) \to 0$. 结合 $U_3(\xi)$ 的连续性可知, $U_{3n}(\xi)$$\mathbb{R}$ 上局部一致收敛于 $0$. 故由(2.3)的第三个方程和 $U_1(\xi), U_2(\xi)$ 的有界性可以得到 $U_{3n}'(\xi)$ 也在 $\mathbb{R}$ 上局部一致收敛于 $0$. 利用引理 3.2-3.4 (上下解的定义), 不难得到 $\lim\limits_{\xi \to -\infty} U_1(\xi) = U_{10}$$\lim\limits_{\xi \to -\infty} U_2(\xi) = U_{20}$.

$\psi_n(\xi) := \dfrac{U_{3n}(\xi)}{U_{3n}(0)}$, 利用引理 3.10 以及 Gronwall 不等式容易证明 $\psi_n(\xi)$ 一致有界, 再结合 Arzela-Ascoli 定理可知 $\psi_n(\xi)$$\mathbb{R}$ 上局部一致收敛, 从而

$\begin{equation} \psi_n'(\xi) = \dfrac{U_{3n}'(\xi)}{U_{3n}(0)} = \dfrac{U_{3n}'(\xi)}{U_{3n}(\xi)} \psi_n(\xi) \end{equation}$

$\mathbb{R}$ 上局部一致收敛, 不妨记为 $\psi_n(\xi) \to \psi_\infty(\xi)$, $\psi_n'(\xi) \to \psi_\infty'(\xi)$, 即存在 $N$, 使得当 $n > N$ 时有 $\lim\limits_{n \to +\infty} \psi_n(\xi) = \psi_\infty(\xi)$, $\lim\limits_{n \to +\infty} \psi_n'(\xi) = \psi_\infty'(\xi)$, 故在(2.3)的第三个方程中令 $n \to +\infty$ 可得

$\begin{equation} c\psi_\infty'(\xi) = d_3 \int_{\mathbb{R}} \mathcal{J}(y) \psi_\infty(\xi - y) \mathrm{d}y + (\beta_1 U_{10} + \beta_2 U_{20}) \int_{0}^{\tau} K(s) \psi_\infty(\xi - cs) \mathrm{d}s - (d_3 + \gamma + \mu_3) \psi_\infty(\xi). \end{equation}$

$U_{3n}(\xi) \geq 0$ 可知 $\psi_\infty(\xi) \geq 0$.若存在某点 $\xi_0$, 使得 $\psi_\infty(\xi_0) = 0$, 则由(3.30)可知 $\psi_\infty'(\xi_0) = 0$, 且当 $\xi < \xi_0$$\psi_\infty(\xi) > 0$, 将 $\xi = \xi_0$ 代入(3.31)可得

$ 0 = d_3 \int_{\mathbb{R}} \mathcal{J}(y) \psi_\infty(\xi_0 - y) \mathrm{d}y + (\beta_1 U_{10} + \beta_2 U_{20}) \int_{0}^{\tau} K(s) \psi_\infty(\xi_0 - cs) \mathrm{d}s > 0, $

这出现了矛盾. 从而对任意的 $\xi \in \mathbb{R}$, $\psi_\infty(\xi) > 0$.

$Z(\xi) := \dfrac{\psi_\infty'(\xi)}{\psi_\infty(\xi)}$, 结合(3.31)可以验证 $Z(\xi)$ 满足

$ \begin{split} cZ(\xi) &= d_3 \int_{\mathbb{R}} \mathcal{J}(y) \dfrac{\psi_\infty(\xi - y)}{\psi_\infty(\xi)} \mathrm{d}y + (\beta_1 U_{10} + \beta_2 U_{20}) \int_{0}^{\tau} K(s) \dfrac{\psi_\infty(\xi - cs)}{\psi_\infty(\xi)} \mathrm{d}s - (d_3 + \gamma + \mu_3) \\ &= d_3 \int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{\int_{\xi}^{\xi - y} Z(t) \mathrm{d}t} \mathrm{d}y + (\beta_1 U_{10} + \beta_2 U_{20}) \int_{0}^{\tau} K(s) \mathrm{e}^{\int_{\xi}^{\xi - cs} Z(t) \mathrm{d}t} \mathrm{d}s - (d_3 + \gamma + \mu_3). \end{split} $

定义

$ g(\lambda, c) = d_3 \int_{\mathbb{R}} \mathcal{J}(y) \mathrm{e}^{-\lambda y} \mathrm{d}y - c\lambda + (\beta_1 U_{10} + \beta_2 U_{20}) \int_{0}^{\tau} K(s) \mathrm{e}^{\int_{\xi}^{\xi - cs} Z(t) \mathrm{d}t} \mathrm{d}s - (d_3 + \gamma + \mu_3), $

类似引理 3.13 的讨论可知 $g(\lambda, c) = 0$ 有两个正根, 不妨分别记为 $\mu_1, \mu_2$$\mu_1 < \mu_2$. 另外, 由命题 3.1 可得 $Z(\pm\infty)$ 存在且 $g(Z(\pm\infty), c) = 0$, 故 $Z(\pm\infty) = \mu_i$$(i = 1 \text{ 或 } 2)$. 从而结合 $Z(\xi)$ 的定义可得 $\psi_\infty'(\pm\infty) > 0$. 类似文献[17] 中引理 3.3 的证明过程可知, 若存在 $\xi^* \in \mathbb{R}$ 使得 $Z(\xi^*) = \inf\limits_{\xi \in \mathbb{R}} Z(\xi)$, 则存在常数 $z_0$ 使得 $Z(\xi) \equiv z_0$, 即 $z_0 = \mu_i\ (i = 1 \text{ 或 } 2)$. 因此, $\inf\limits_{\xi \in \mathbb{R}} Z(\xi) \geq \min\{ Z(+\infty), Z(-\infty) \} > 0$. 利用 $Z(\xi)$ 的定义可得

$ 0 < Z(0) = \dfrac{\psi_\infty'(0)}{\psi_\infty(0)} = \lim_{n \to \infty} \left( \dfrac{U_{3n}'(0)}{U_{3n}(0)} \psi_n(0) \right) \dfrac{1}{\psi_\infty(0)} = \lim_{n \to \infty} \dfrac{U_{3n}'(0)}{U_{3n}(0)}, $

因为 $\lim\limits_{n \to +\infty} U_{3n}'(0) > 0$, 则由保号性可知 $U_{3n}'(0) > 0$, 从而 $U_3'(\xi_n) = U_{3n}'(0) > 0$, 这与假设 $U_3'(\xi_n) \leq 0$ 矛盾. 证毕.

定理 3.1$(A_1)$-$(A_2)$ 成立, 则当 $R_0 > 1$, $c > c^*$ 时, 对任意的 $\xi \in \mathbb{R}$, (2.3)存在满足(2.4)的解 $(U_1(\xi), U_2(\xi), U_3(\xi))$.

由引理 3.1-3.9 可知(2.3)存在解, 且满足$\lim\limits_{\xi \to -\infty} \bigl(U_1(\xi), U_2(\xi), U_3(\xi)\bigr) = (U_{10}, U_{20}, 0)$,

故仅需证明$\lim\limits_{\xi \to +\infty} \bigl(U_1(\xi), U_2(\xi), U_3(\xi)\bigr) = (U_1^*, U_2^*, U_3^*)$.

事实上, 由引理 3.14 和引理 3.15 可得, $U_i(\xi) > 0$ ($i=1,2,3$).$a(x) = x - 1 - \ln x$, $\sigma^+(y) = \int_y^{+\infty} \mathcal{J}(x)\,\mathrm{d}x, \sigma^-(y) = \int_{-\infty}^y \mathcal{J}(x)\,\mathrm{d}x$. 由于 $ \mathcal{J}(\cdot)$ 具有紧支集且 $r$$ \mathcal{J}(\cdot)$ 的支集半径, 则当 $|y| \geq r$ 时, 有

$\begin{matrix} \sigma^+(y) \equiv 0 \quad \text{和} \quad \sigma^-(y) \equiv 0. \end{matrix}$

定义 Lyapunov 函数

$ L(U_1, U_2, U_3)(\xi) = c U_1^* L_1(\xi) + c U_2^* L_2(\xi) + c U_3^* L_3(\xi) + d_1 U_1^* V_1(\xi) + d_2 U_2^* V_2(\xi) + d_3 U_3^* V_3(\xi), $

其中

$ \begin{aligned} L_1(\xi) &= a\left( \frac{U_1(\xi)}{U_1^*} \right), \quad L_2(\xi) = a\left( \frac{U_2(\xi)}{U_2^*} \right),\\ L_3(\xi) &= a\left( \frac{U_3(\xi)}{U_3^*} \right) + (\mu_3 + r) U_3^* \int_0^r K(s) \int_0^{cs} a\left( \frac{U_3(\xi - \theta)}{U_3^*} \right) \mathrm{d}\theta\,\mathrm{d}s,\\ V_1(\xi) &= \int_0^{+\infty} \sigma^+(y) \, a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y - \int_{-\infty}^0 \sigma^-(y) \, a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y,\\ V_2(\xi) &= \int_0^{+\infty} \sigma^+(y) a\left( \frac{U_2(\xi - y)}{U_2^*} \right) \mathrm{d}y - \int_{-\infty}^0 \sigma^-(y) a\left( \frac{U_2(\xi - y)}{U_2^*} \right) \mathrm{d}y, \\ V_3(\xi) &= \int_0^{+\infty} \sigma^+(y) a\left( \frac{U_3(\xi - y)}{U_3^*} \right) \mathrm{d}y - \int_{-\infty}^0 \sigma^-(y) a\left( \frac{U_3(\xi - y)}{U_3^*} \right) \mathrm{d}y. \end{aligned} $

由文献[18] 中的定理 1, $U_i(\xi) > 0$ ($i = 1,2,3$) 并结合 $a(x)$$x > 0$ 时有下界的事实可知, $L_1(\xi)$, $L_2(\xi)$$L_3(\xi)$ 有下界. 再结合(2.3), 引理 3.14 和引理 3.15 可知, $V_1(\xi)$, $V_2(\xi)$$V_3(\xi)$ 也有下界, 即 $L(U_1, U_2, U_3)(\xi)$ 有下界.

注意到, $\sigma^+(0)=\frac{1}{2}$, $\frac{\mathrm{d}\sigma^+(y)}{\mathrm{d}y}=- \mathcal{J}(y)$$\frac{\mathrm{d}\sigma^-(y)}{\mathrm{d}y}= \mathcal{J}(y)$, 则

$\begin{matrix} \begin{aligned} \frac{\mathrm{d}V_1(\xi)}{\mathrm{d}\xi} &= \frac{\mathrm{d}}{\mathrm{d}\xi} \int_0^{+\infty}\sigma^+(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y - \frac{\mathrm{d}}{\mathrm{d}\xi} \int_{-\infty}^0 \sigma^-(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y \\ &= \int_0^{+\infty} \sigma^+(y) \frac{\mathrm{d}}{\mathrm{d}\xi} a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y - \int_{-\infty}^0 \sigma^-(y) \frac{\mathrm{d}}{\mathrm{d}\xi} a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y \\ &= \int_0^{+\infty} \sigma^+(y) \left[ -\frac{\mathrm{d}}{\mathrm{d}y} a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \right] \mathrm{d}y - \int_{-\infty}^0 \sigma^-(y) \left[ -\frac{\mathrm{d}}{\mathrm{d}y} a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \right] \mathrm{d}y \\ &= -\left[ \sigma^+(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \right]_0^{+\infty} + \int_0^{+\infty} \frac{\mathrm{d}\sigma^+(y)}{\mathrm{d}y} a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y \\ &\quad + \left[ \sigma^-(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \right]_{-\infty}^0 - \int_{-\infty}^0 \frac{\mathrm{d}\sigma^-(y)}{\mathrm{d}y} a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y \\ &= a\left( \frac{U_1(\xi)}{U_1^*} \right) - \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y. \end{aligned} \end{matrix}$

同理可得,

$\begin{gather*} \frac{\mathrm{d}V_2(\xi)}{\mathrm{d}\xi} = a\left( \frac{U_2(\xi)}{U_2^*} \right) - \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_2(\xi - y)}{U_2^*} \right) \mathrm{d}y, \\ \frac{\mathrm{d}V_3(\xi)}{\mathrm{d}\xi} = a\left( \frac{U_3(\xi)}{U_3^*} \right) - \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_3(\xi - y)}{U_3^*} \right) \mathrm{d}y. \end{gather*}$

另外, 通过计算可得

$ \begin{split} & ~~~~\frac{\mathrm{d}}{\mathrm{d}\xi} \int_{0}^{\tau} K(s) \int_{0}^{cs} a\left( \frac{U_3(\xi - \theta)}{U_3^*} \right) \mathrm{d}\theta \mathrm{d}s \\ &= \frac{U_3(\xi)}{U_3^*} - \frac{1}{U_3^*} \int_{0}^{\tau} K(s) U_3(\xi - cs) \mathrm{d}s + \int_{0}^{\tau} K(s) \ln \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s. \end{split} $

从而

$ \begin{aligned} \frac{\mathrm{d}L(\xi)}{\mathrm{d}\xi} &= \left( 1 - \frac{U_1^*}{U_1(\xi)} \right) \left[ d_1 ( \mathcal{J} * U_1(\xi) - U_1(\xi)) + \Lambda - \beta_1 U_1(\xi) \int_0^r K(s) U_3(\xi - cs) \mathrm{d}s \right. \\ &\quad \left. - (\alpha + \mu_1) U_1(\xi) \right] \\ &\quad + \left( 1 - \frac{U_2^*}{U_2(\xi)} \right) \left[ d_2 ( \mathcal{J} * U_2(\xi) - U_2(\xi)) + \alpha U_1(\xi) - \beta_2 U_2(\xi) \int_0^r K(s) U_3(\xi - cs) \mathrm{d}s \right. \\ &\quad \left. - (\gamma_1 + \mu_2) U_1(\xi) \right] \\ &\quad + \left( 1 - \frac{U_3^*}{U_3(\xi)} \right) \left[ d_3 ( \mathcal{J} * U_3(\xi) - U_3(\xi)) - \beta_1 U_1(\xi) \int_0^r K(s) U_3(\xi - cs) \mathrm{d}s \right. \\ &\quad \left. - \beta_2 U_2(\xi) \int_0^r K(s) U_3(\xi - cs) \mathrm{d}s - (\gamma + \mu_3) U_3(\xi) \right] \\ &\quad + (\mu_3 + \gamma) U_3^* \left[ \frac{U_3(\xi)}{U_3^*} - \frac{1}{U_3^*} \int_0^r K(s) U_3(\xi - cs) \mathrm{d}s + \int_0^r K(s) \ln \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s \right] \\ &\quad + d_1 U_1^* a\left( \frac{U_1(\xi)}{U_1^*} \right) + d_2 U_2^* a\left( \frac{U_2(\xi)}{U_2^*} \right) + d_3 U_3^* a\left( \frac{U_3(\xi)}{U_3^*} \right) \\ &\quad - d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y - d_2 U_2^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_2(\xi - y)}{U_2^*} \right) \mathrm{d}y \\ &\quad - d_3 U_3^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_3(\xi - y)}{U_3^*} \right) \mathrm{d}y \\ &:= \mathrm{B}_1 + \mathrm{B}_2, \end{aligned} $

其中

$ \begin{aligned} \mathrm{B}_1 &= \left(1 - \frac{U_1^*}{U_1(\xi)}\right) d_1\bigl(\mathcal{J} * U_1(\xi) - U_1(\xi)\bigr) - d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_1(\xi-y)}{U_1^*} \right) \mathrm{d}y \\ &\quad + \left(1 - \frac{U_2^*}{U_2(\xi)}\right) d_2\bigl(\mathcal{J} * U_2(\xi) - U_2(\xi)\bigr) - d_2 U_2^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_2(\xi-y)}{U_2^*} \right) \mathrm{d}y \\ &\quad + \left(1 - \frac{U_3^*}{U_3(\xi)}\right) d_3\bigl(\mathcal{J} * U_3(\xi) - U_3(\xi)\bigr) - d_3 U_3^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_3(\xi-y)}{U_3^*} \right) \mathrm{d}y \\ &\quad + d_1 U_1^* a\left( \frac{U_1(\xi)}{U_1^*} \right) + d_2 U_2^* a\left( \frac{U_2(\xi)}{U_2^*} \right) + d_3 U_3^* a\left( \frac{U_3(\xi)}{U_3^*} \right), \end{aligned} $
$ \begin{aligned} \mathrm{B}_2 &= \left(1 - \frac{U_1^*}{U_1(\xi)}\right) \left[ \Lambda - \beta U_1(\xi) \int_0^\tau K(s) U_3(\xi - cs) \mathrm{d}s - (\alpha + \mu_1) U_1(\xi) \right] \\ &\quad + \left(1 - \frac{U_2^*}{U_2(\xi)}\right) \left[ \alpha U_1(\xi) - \mu_2 U_2(\xi) - \beta_2 U_2(\xi) \int_0^\tau K(s) U_3(\xi - cs) \mathrm{d}s \right] \\ &\quad + \left(1 - \frac{U_3^*}{U_3(\xi)}\right) \left[ (\beta_1 U_1(\xi) - \beta_2 U_2(\xi)) \int_0^\tau K(s) U_3(\xi - cs) \mathrm{d}s - (\gamma + \mu_3) U_3(\xi) \right] \\ &\quad + (\mu_3 + \gamma) U_3^* \left[ \frac{U_3(\xi)}{U_3^*} - \frac{1}{U_3^*} \int_0^\tau K(s) U_3(\xi - cs) \mathrm{d}s + \int_0^\tau K(s) \ln \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s \right]. \end{aligned} $

利用 $\ln \frac{U_1(\xi)}{U_1^*} = \ln \frac{U_1(\xi - y)}{U_1^*} - \ln \frac{U_1(\xi - y)}{U_1(\xi)}$, 则对 $\mathrm{B}_1$ 中的第一项有

$ \begin{aligned} & \left( 1 - \frac{U_1^*}{U_1(\xi)} \right) d_1 \bigl( \mathcal{J} * U_1(\xi) - U_1(\xi) \bigr) + d_1 U_1^* a\left( \frac{U_1(\xi)}{U_1^*} \right) - d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y \\ &= d_1 \int_{-\infty}^{+\infty} \mathcal{J}(y) \bigl[ U_1(\xi - y) - U_1(\xi) \bigr] \mathrm{d}y - d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) \left[ \frac{U_1(\xi - y)}{U_1(\xi)} - 1 \right] \mathrm{d}y \\ &\quad + d_1 U_1^* \left( \frac{U_1(\xi)}{U_1^*} - 1 - \ln \frac{U_1(\xi)}{U_1^*} \right) - d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y \\ &= d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) \left[ \frac{U_1(\xi - y)}{U_1^*} - \frac{U_1(\xi - y)}{U_1(\xi)} - \ln \frac{U_1(\xi)}{U_1^*} \right] \mathrm{d}y - d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y \\ &= d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) \left[ \frac{U_1(\xi - y)}{U_1^*} - \frac{U_1(\xi - y)}{U_1(\xi)} - \left( \ln \frac{U_1(\xi - y)}{U_1^*} - \ln \frac{U_1(\xi - y)}{U_1(\xi)} \right) - 1 + 1 \right] \mathrm{d}y\\ & - d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y \\ &= d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) \left[ a\left( \frac{U_1(\xi - y)}{U_1^*} \right) - a\left( \frac{U_1(\xi - y)}{U_1(\xi)} \right) \right] \mathrm{d}y - d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y \\ &= - d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y. \end{aligned} $

$\begin{matrix} \mathrm{B}_1 =& - d_1 U_1^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_1(\xi - y)}{U_1^*} \right) \mathrm{d}y - d_2 U_2^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_2(\xi - y)}{U_2^*} \right) \mathrm{d}y \notag \\ &- d_3 U_3^* \int_{-\infty}^{+\infty} \mathcal{J}(y) a\left( \frac{U_3(\xi - y)}{U_3^*} \right) \mathrm{d}y. \end{matrix}$

此外, 通过计算可得

$\begin{matrix} \begin{aligned} B_2 &= \mu_1 U_1^* \left( 2 - \frac{U_1(\xi)}{U_1^*} - \frac{U_1^*}{U_1(\xi)} \right) - \beta_1 U_1^* U_3^* a\left( \frac{U_1(\xi) \int_0^\tau K(s) U_3(\xi - cs) \mathrm{d}s}{U_1^* U_3(\xi)} \right) \\ &\quad - \beta_2 U_2^* U_3^* \left[ a\left( \frac{U_2(\xi) \int_0^\tau K(s) U_3(\xi - cs) \mathrm{d}s}{U_2^* U_3(\xi)} \right) + a\left( \frac{U_1(\xi) U_2^*}{U_1^* U_2(\xi)} \right) \right] \\ &\quad - \mu_2 U_2^* \left[ a\left( \frac{U_2(\xi)}{U_2^*} \right) + a\left( \frac{U_1(\xi) U_2^*}{U_1^* U_2(\xi)} \right) \right] - (\alpha U_1^* + \beta U_1^* U_3^*) a\left( \frac{U_1^*}{U_1(\xi)} \right) \\ &\quad + \beta_1 U_1^* U_3^* \int_0^\tau K(s) \ln \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s - \beta_1 U_1^* U_3^* \ln \left( \int_0^\tau K(s) \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s \right) \\ &\quad + \beta_2 U_2^* U_3^* \int_0^\tau K(s) \ln \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s - \beta_2 U_2^* U_3^* \ln \left( \int_0^\tau K(s) \frac{U_3(\xi - cs)}{U_3(\xi)} \mathrm{d}s \right). \end{aligned} \end{matrix}$

结合(3.34)和(3.35)可知 $L(\xi)$ 关于 $\xi$ 单调递减. 接下来, 考虑递增正序列 $\{\xi_n\}_{n \in \mathbb{N}}$ 且满足 $\lim_{n \to \infty} \xi_n = +\infty$. 定义

$ \{ U_{1n}(\xi) = U_1(\xi + \xi_n) \}_{n \in \mathbb{N}}, \quad \{ U_{2n}(\xi) = U_2(\xi + \xi_n) \}_{n \in \mathbb{N}}, \quad \{ U_{3n}(\xi) = U_3(\xi + \xi_n) \}_{n \in \mathbb{N}}, $

$U_{1n} \to U_{1\infty}$, $U_{2n} \to U_{2\infty}$$U_{3n} \to U_{3\infty}$. 因为 $L(U_1, U_2, U_3)(\xi)$ 关于 $\xi$ 单调递减有下界, 则存在常数 $\hat{C}$ 以及足够大的 $n \in \mathbb{N}^*$, 使得

$ \hat{C} \leq L(U_{1n}, U_{2n}, U_{3n})(\xi) = L(U_1, U_2, U_3)(\xi + \xi_n) \leq L(U_1, U_2, U_3)(\xi), $

故存在实数 $M \in \mathbb{R}$, 使对任意的 $\xi \in \mathbb{R}$$\lim\limits_{n \to +\infty} L(U_{1n}, U_{2n}, U_{3n})(\xi) = M$. 结合 Lebegue 控制收敛定理可得, 对任意的 $\xi \in \mathbb{R}$, 有 $\lim\limits_{n \to +\infty} L(U_{1n}, U_{2n}, U_{3n})(\xi) = L(U_{1\infty}, U_{2\infty}, U_{3\infty})(\xi)$, 于是 $L(U_{1\infty}, U_{2\infty}, U_{3\infty})(\xi) = M$. 注意到 $\frac{\mathrm{d}L}{\mathrm{d}\xi} = 0$ 当且仅当 $U_1(\xi) \equiv U_1^*$, $U_2(\xi) \equiv U_2^*$, $U_3(\xi) \equiv U_3^*$, 也即 $(U_{1\infty}, U_{2\infty}, U_{3\infty}) \equiv (U_1^*, U_2^*, U_3^*)$. 证毕.

定理 3.2$(A_1)-(A_2)$ 成立, 则当 $R_0 > 1$, $c = c^*$ 时, 对任意的 $\xi \in \mathbb{R}$, (2.3)存在满足(2.4)的解 $\bigl(U_1(\xi), U_2(\xi), U_3(\xi)\bigr)$.

定理 3.2 的证明与文献[14]中定理 3.1 的证明类似, 故此省略.

4 行波解的不存在性

本节建立当 $R_0 > 1$, $0 < c < c^*$ 时(2.1)行波解的不存在性. 为了方便, 记

$ \begin{cases} F_1(u_1, u_2, u_3, u_4) = \Lambda - \beta_1 u_1(x,t) \int_0^\tau K(s) u_3(x,t-s) \mathrm{d}s - (\alpha + \mu_1) u_1(x,t), \\ F_2(u_1, u_2, u_3, u_4) = -\beta_2 u_2(x,t) \int_0^\tau K(s) u_3(x,t-s) \mathrm{d}s + \alpha u_1(x,t) - (\gamma_1 + \mu_2) u_2(x,t), \\ F_3(u_1, u_2, u_3, u_4) = \beta u_1(x,t) \int_0^\tau K(s) u_3(x,t-s) \mathrm{d}s + \beta_2 u_2(x,t) \int_0^\tau K(s) u_3(x,t-s) \mathrm{d}s \\ ~~~~~~~~~~~~~~~~~~~~~~~~~- (\gamma + \mu_3) u_3(x,t), \\ F_4(u_1, u_2, u_3, u_4) = \gamma_1 u_2(x,t) + \gamma u_3(x,t) - \mu_4 u_4(x,t). \end{cases} $

不难验证 $\frac{\partial F_3}{\partial u_1} > 0$, $\frac{\partial F_3}{\partial u_2} > 0$$\frac{\partial F_3}{\partial u_4} = 0$, 即 $F_3(u_1, u_2, u_3, u_4)$ 关于 $u_1$, $u_2$$u_4$ 是单调递增的.

定理 4.1$(A_1)-(A_2)$ 成立, 则当 $R_0 > 1$$0 < c < c^*$ 时, (2.3)不存在满足(2.4)的解.

利用反证法. 不妨设当 $0 < c < c^*$ 时,(2.3)存在满足渐近边界条件(2.4)的非平凡解 $\bigl(U_1(\xi), U_2(\xi), U_3(\xi)\bigr)$. 由引理 3.14 可知 $\bigl(U_1(\xi), U_2(\xi), U_3(\xi)\bigr)$ 有界, 故存在常数 $\hat{\delta}_1 > 0$, $\hat{\delta}_2 > 0$$\widetilde{M} > 0$ 使得对任意的 $\xi \in \mathbb{R}$$U_1(\xi) \geq \hat{\delta}_1$, $U_2(\xi) \geq \hat{\delta}_2$$U_3(\xi) \leq \widetilde{M}$, 且对任意小的正数 $\varepsilon_0 > 0$, 存在充分大的常数 $M_\varepsilon > 0$ 使得当 $\xi < -M_\varepsilon$ 时, 有 $0 < U_{10} - \varepsilon \leq U_1(\xi) \leq U_{10}$, $0 < U_{20} - \varepsilon \leq U_2(\xi) \leq U_{20}$. 因此, 由(2.3)的第三个式子可知, 当 $\xi < -M_\varepsilon$ 时, 有

$\begin{matrix} \begin{aligned} c U_3'(\xi) &\geq d_3 \bigl( \mathcal{J} * U_3(\xi) - U_3(\xi) \bigr) + \beta_1 (U_{10} - \varepsilon) \int_0^\tau K(s) U_3(\xi - c_1 s) \mathrm{d}s \\ &\quad + \beta_2 (U_{20} - \varepsilon) \int_0^\tau K(s) U_3(\xi - c_1 s) \mathrm{d}s - (\gamma + \mu_3) U_3(\xi). \end{aligned} \end{matrix}$

另外, 当 $\xi > -M_\varepsilon$ 时, 有 $0 < \frac{U_{10} - \varepsilon}{U_1(\xi)} \leq \frac{U_{10} - \varepsilon}{\hat{\delta}_1} < +\infty$. 因为 $U_3(\xi) > 0$ 以及 $U_3(+\infty) = U_3^* > 0$, 故存在常数 $M^* > 0$ 使得对所有的 $\xi > -M_\varepsilon$, 有 $M^* \leq U_3(\xi) \leq U_3^*$. 因此, 存在充分大的自然数 $k > 1$ 使得对任意的 $\xi > -M_\varepsilon$, $\frac{U_{10} - \varepsilon}{\bigl(1 + U_3(\xi - c_1 s)\bigr)^k} \leq U_1(\xi)$. 同理 $\frac{U_{20} - \varepsilon}{\bigl(1 + U_3(\xi - c_1 s)\bigr)^k} \leq U_2(\xi)$. 从而利用(2.3)的第三个式子可知, 当 $\xi > -M_\varepsilon$ 时, 有

$\begin{matrix} \begin{aligned} c_1 U_3'(\xi) &\geq d_3 \bigl( \mathcal{J} * U_3(\xi) - U_3(\xi) \bigr) + \beta_1 (U_{10} - \varepsilon) \int_0^\tau K(s) \frac{U_3(\xi - c_1 s)}{\bigl(1 + U_3(\xi - c_1 s)\bigr)^k} \mathrm{d}s \\ &\quad + \beta_2 (U_{20} - \varepsilon) \int_0^\tau K(s) \frac{U_3(\xi - c_1 s)}{\bigl(1 + U_3(\xi - c_1 s)\bigr)^k} \mathrm{d}s - (\gamma + \mu_3) U_3(\xi). \end{aligned} \end{matrix}$

结合(4.1)和(4.2)可得, 对任意的 $\xi \in \mathbb{R}$, 有

$\begin{matrix} \begin{aligned} c_1 U_3'(\xi) &\geq d_3 \bigl( \mathcal{J} * U_3(\xi) - U_3(\xi) \bigr) + \beta_1 (U_{10} - \varepsilon) \int_0^\tau K(s) \frac{U_3(\xi - c_1 s)}{\bigl(1 + U_3(\xi - c_1 s)\bigr)^k} \mathrm{d}s \\ &\quad + \beta_2 (U_{20} - \varepsilon) \int_0^\tau K(s) \frac{U_3(\xi - c_1 s)}{\bigl(1 + U_3(\xi - c_1 s)\bigr)^k} \mathrm{d}s - (\gamma + \mu_3) U_3(\xi). \end{aligned} \end{matrix}$

$u(x,t) = U_3(x + c_1 t)$, 且 $v(x,t)$ 是初值问题

$\begin{equation} \begin{cases} \dfrac{\partial v(x,t)}{\partial t} = d_3 \left( \mathcal{J} * v(x,t) - v(x,t) \right) + \int_0^\tau K(s) b_1 \left( v(x,t-s) \right) \mathrm{d}s \\ \quad\quad\quad\quad~~+ \int_0^\tau K(s) b_2 \left( v(x,t-s) \right) \mathrm{d}s - (\gamma + \mu_3) v(x,t), \, x \in \mathbb{R}, \, t \geq 0, \\ v(x,s) = U_3 \left( x + c_1 s \right), \, x \in \mathbb{R}, \, s \in [-\tau, 0] \end{cases} \end{equation}$

的解. 记 $b_1(u) = \inf\limits_{u \leq v \leq \widetilde{M}} \left\{ \beta_1 (U_{10} - \varepsilon) \frac{v}{(1 + v)^k} \right\}$$b_2(u) = \inf\limits_{u \leq v \leq \widetilde{M}} \left\{ \beta_2 (U_{20} - \varepsilon) \frac{v}{(1 + v)^k} \right\}$. 由(4.3)可知对任意的 $x \in \mathbb{R}$$t \geq 0$, 有

$ \begin{cases} \dfrac{\partial u(x,t)}{\partial t} \geq d_3 \left( \mathcal{J} * u(x,t) - u(x,t) \right) + \int_0^\tau K(s) b_1 \left( u(x,t-s) \right) \mathrm{d}s \\ \quad\quad\quad\quad~~+ \int_0^\tau K(s) b_2 \left( u(x,t-s) \right) \mathrm{d}s - (\gamma + \mu_3) u(x,t), \, x \in \mathbb{R}, \, t \geq 0, \\ u(x,s) = U_3 \left( x + c_1 s \right), \, x \in \mathbb{R}, \, s \in [-\tau, 0]. \end{cases} $

结合 $F_3$ 关于 $u_1$, $u_2$$u_4$ 的单调性和比较原理[19]可知, 对任意的 $x \in \mathbb{R}$$t \geq 0$, 有 $u(x,t) \geq v(x,t)$. 利用渐近传播理论, 类似文献[12]中定理 6 的证明可得 $\liminf\limits_{t \to +\infty |x| \leq \hat{c} t} v(x,t) > 0$, 其中 $\hat{c} \in (0, c^*)$.$c_0 \in (c_1, c^*)$, 令 $x = -c_0 t$, 则

$\begin{matrix} \begin{aligned} \liminf_{t \to +\infty} u(x,t) \geq \liminf\limits_{t \to +\infty |x| \leq \hat{c} t} v(x,t) > 0. \end{aligned} \end{matrix}$

注意到, 当 $t \to +\infty$$\xi = x + c_1 t = (c_1 - c_0)t$. 此时, $\lim\limits_{t \to +\infty} u(x,t) = \lim\limits_{t \to +\infty} U_3(x + c_1 t) = 0$, 这与$(4.5) 矛盾. 故假设不成立. 定理证毕.

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This work is devoted to study the evolution properties of the solutions with compactly supported initial data of a time-periodic S-I reaction-diffusion epidemic model with distributed delays by using the theory of asymptotic spreading speed, by which we can explain the geographic spreading phenomena of newly introduced diseases. Firstly, by applying the uniform persistence idea and comparison skill, and taking three steps, we prove the uniform persistence of the model system in the region where the disease has invaded. Along the way, the main difficulty caused by delay and the periodicity of the coefficients is solved by constructing initial boundary value problems posed on truncated intervals. Secondly, we analyze the evolution properties of the host population in the disease-free region by constructing monotone equation and further employing the spreading speed theory of monotone systems combining with the comparison principle.

Bai Z, Zhang S.

Traveling waves of a diffusive SIR epidemic model with a class of nonlinear incidence rates and distributed delay

Communications in Nonlinear Science and Numerical Simulation, 2015, 22(1-3): 1370-1381

DOI:10.1016/j.cnsns.2014.07.005      URL     [本文引用: 1]

Hu H, Zou X.

Traveling waves of a diffusive SIR epidemic model with general nonlinear incidence and infinitely distributed latency but without demography

Nonlinear Analysis: Real World Applications, 2021, 58: Art 103224

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程悦玲. 几类时滞扩散型流行病模型的行波解. 江苏: 江苏大学, 2020

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Cheng Y L. The Traveling Wave Solutions of Some Diffusive Epidemic Models with Delay. Jiangsu: Jiangsu University, 2020

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Wu W, Teng Z.

Traveling waves in nonlocal dispersal SIR epidemic model with nonlinear incidence and distributed latent delay

Advances in Difference Equations, 2020, 2020(1): Art 614

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Zhang C, Gao J, Sun H, et al.

Dynamics of a reaction-diffusion SVIR model in a spatial heterogeneous environment

Physica A: Statistical Mechanics and its Applications, 2019, 533: Art 122049

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Zhang R, Liu S.

Traveling waves for SVIR epidemic model with nonlocal dispersal

Math Biosci Eng, 2019, 16(3): 1654-1682

DOI:10.3934/mbe.2019079      PMID:30947437      [本文引用: 8]

In this paper, we studied an SVIR epidemic model with nonlocal dispersal and delay, and we find that the existence of traveling wave is determined by the basic reproduction number ℜ₀ and minimal wave speed c. By applying Schauder's fixed point theorem and Lyapunov functional, the existence and boundary asymptotic behaviour of traveling wave solutions is investigated for ℜ₀>1 and c>c. The existence of traveling waves is obtained for ℜ₀>1 and c=c by employing a limiting argument. We also show that the nonexistence of traveling wave solutions by Laplace transform. Our results imply that (i) the diffusion and infection ability of infected individuals can accelerate the wave speed; (ii) the latent period and successful rate of vaccination can slow down the wave speed.

Liao S, Yang W M, Fang F.

Traveling waves for a cholera vaccination model with nonlocal dispersal

Mathematical Methods in the Applied Sciences, 2021, 44(6): 5150-5171

DOI:10.1002/mma.7099      [本文引用: 1]

In this paper, we study the existence and nonexistence of a nonlocal dispersal cholera model with vaccination. First, we explore the existence of traveling wave solution when R-0 > 1 and c >= c* by using the Schauder's fixed-point theorem associated with the upper-lower solutions. Moreover, the Lyapunov functional is used to show the boundary asymptotic behavior of traveling wave solution. Furthermore, in the case when R-0 > 1 and c < c*, we show that the model system has nonexistence of traveling wave solution on the basis of the Laplace transform. At last, we discuss how the spatial movement and vaccination affect the minimal wave speed.

李孝武, 杨赟瑞, 刘凯凯.

一类时滞非局部扩散 SVIR 模型单稳行波解的稳定性

浙江大学学报 (理学版), 2023, 50(3): 273-286

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Li X W, Yang Y R, Liu K K.

Stability of monostable traveling waves for a class of SVIR models with nonlocal diffusion and delay

Journal of Zhejiang University (Science Edition), 2023, 50(3): 273-286

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Zhang G B, Li W T, Wang Z C.

Spreading speeds and traveling waves for nonlocal dispersal equations with degenerate monostable nonlinearity

Journal of Differential Equations, 2012, 252(9): 5096-5124

DOI:10.1016/j.jde.2012.01.014      URL     [本文引用: 3]

Huang G, Takeuchi Y, Ma W, et al.

Global stability for delay SIR and SEIR epidemic models with nonlinear incidence rate

Bulletin of Mathematical Biology, 2010, 72(5): 1192-1207

DOI:10.1007/s11538-009-9487-6      PMID:20091354      [本文引用: 1]

In this paper, based on SIR and SEIR epidemic models with a general nonlinear incidence rate, we incorporate time delays into the ordinary differential equation models. In particular, we consider two delay differential equation models in which delays are caused (i) by the latency of the infection in a vector, and (ii) by the latent period in an infected host. By constructing suitable Lyapunov functionals and using the Lyapunov-LaSalle invariance principle, we prove the global stability of the endemic equilibrium and the disease-free equilibrium for time delays of any length in each model. Our results show that the global properties of equilibria also only depend on the basic reproductive number and that the latent period in a vector does not affect the stability, but the latent period in an infected host plays a positive role to control disease development.

Pan S, Li W T, Lin G.

Existence and stability of traveling wavefronts in a nonlocal diffusion equation with delay. Nonlinear Analysis: Theory

Methods & Applications, 2010, 72(6): 3150-3158

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