\documentclass[reqno]{amsart} \usepackage{hyperref} \AtBeginDocument{{\noindent\small \emph{Electronic Journal of Differential Equations}, Vol. 2012 (2012), No. 38, pp. 1--22.\newline ISSN: 1072-6691. URL: http://ejde.math.txstate.edu or http://ejde.math.unt.edu \newline ftp ejde.math.txstate.edu} \thanks{\copyright 2012 Texas State University - San Marcos.} \vspace{9mm}} \begin{document} \title[\hfilneg EJDE-2012/38\hfil Existence and stability of periodic solutions] {Existence and stability of periodic solutions of BAM high-order Hopfield neural networks with impulses and delays on time scales} \author[W. Yang \hfil EJDE-2012/38\hfilneg] {Wengui Yang} \address{Wengui Yang \newline Ministry of Public Education, Sanmenxia Polytechnic, Sanmenxia 472000, China} \email{yangwg8088@163.com} \thanks{Submitted November 9, 2011. Published March 14, 2012.} \subjclass[2000]{34K13, 34K20, 92B20} \keywords{Bidirectional associative memory; impulses and delays; \hfill\break\indent high-order Hopfield neural networks; existence and stability; time scales} \begin{abstract} By using Mawhins's continuation theorem of coincidence degree theory and constructing some suitable Lyapunov functions, the periodicity and the exponential stability for a class of bidirectional associative memory (BAM) high-order Hopfield neural networks with impulses and delays on time scales are investigated. An example illustrates our results. \end{abstract} \maketitle \numberwithin{equation}{section} \newtheorem{theorem}{Theorem}[section] \newtheorem{lemma}[theorem]{Lemma} \newtheorem{remark}[theorem]{Remark} \newtheorem{example}[theorem]{Example} \allowdisplaybreaks \section{Introduction} The bidirectional associative memory (BAM) neural network models were introduced by Kosko \cite{k1,k2}. It is a special class of recurrent neural networks that can store bipolar vector pairs. The BAM neural network is composed of neurons arranged in two neural fields; i.e., the $F_X$-field and the $F_Y$-field. The neurons in one field are fully interconnected to the neurons in the other field, while there is no interconnection among neurons in the same neural field. Through iterations of forward and backward information flows between the two neural fields, it performs a two-way associative search for stored bipolar vector pairs and generalizes the single-field auto-associative Hebbian correlation to a two-field pattern-matched hetero-associative circuits. Therefore, BAM neural networks possesses good application prospects in many fields such as pattern recognition, parallel computation, image and signal processing, optimization automatic control and artificial intelligence. Recently, BAM neural networks have attracted the attention of many scientists (e.g., mathematicians, physicists, computer scientists and so on) and many results for BAM neural networks with or without axonal signal transmission delays including stability and periodic solutions have been obtained \cite{b1,b9,b3,b4,b2,b5,b7,b8,b6} and the references quoted therein. For example, in Refs. \cite{c2,c3,c4,c1}, the authors discussed the problem of the stability of the BAM neural networks with or without delays, and obtained some sufficient conditions to ensure the stability of equilibrium point. Li \cite{c5}, Ho et al \cite{c6}, Li and Yang \cite{c7}, Chen and Cui \cite{c8}, and Xia et al \cite{c9} discussed the existence and exponential stability of the equilibrium point of several classes of impulsive BAM neural networks using different methods, such as linear matrix inequality (LMI), Fixed point theorem, Halanay inequality, Lyapunov functional method, M-matrix theory and Topological degree methods, respectively. On the other hand, due to the fact that high-order Hopfield neural networks (HHNNs) have stronger approximation property, faster convergence rate, greater storage capacity, and higher fault tolerance than lower-order neural networks, high-order neural networks have been the object of intensive analysis by numerous authors in the recent years. We refer the reader to \cite{1,2,5,6,7,8,3,4,9}. However, to the best of the author's knowledge, few results have been obtained the periodicity and the exponential stability for a class of BAM high-order Hopfield neural networks with impulses and delays on time scales. The objective of this paper is to investigate the existence and stability of periodic solutions of BAM HHNNs with impulses and delays on time scales \begin{equation} \label{e1.1} \begin{gathered} \begin{aligned} x_i^\Delta(t)&= -c_i(t)x_i(t)+\sum_{j=1}^ma_{ij}(t)f_j(y_j(t-\tau_{ij}(t)))\\ &\quad +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}(t)g_j(y_j(t-\sigma_{ijl}(t))) g_l(y_l(t-\upsilon_{ijl}(t)))+I_i(t), \quad t\neq t_k, \end{aligned}\\ \Delta x_i(t_k)= x_i(t_k^+)-x_i(t_k^-)=\alpha_{ik}(x_i(t_k)),\quad i=1,2,\dots,n,\; k=1,2,\dots, \\ \begin{aligned} y_j^\Delta(t)&= -d_j(t)y_j(t)+\sum_{i=1}^ne_{ji}(t)p_i(x_i(t-\hat{\tau}_{ji}(t)))\\ &\quad +\sum_{i=1}^n\sum_{r=1}^nh_{jir}(t)q_i(x_i(t-\hat{\sigma}_{jir}(t))) q_r(x_r(t-\hat{\upsilon}_{jir}(t)))+J_j(t),\quad t\neq t_k, \end{aligned}\\ \Delta y_j(t_k)= y_j(t_k^+)-y_j(t_k^-)=\beta_{jk}(y_j(t_k)),\quad j=1,2,\dots,m,\; k=1,2,\dots, \end{gathered} \end{equation} where $\mathbb{T}$ is an $\omega$-periodic time scale which has the subspace topology inherited from the standard topology on $\mathbb{R}$. And $x_i$ and $y_j$ are the activations of the $i$-th neuron in $F_X$-layer and the $j$th neuron in $F_Y$-layer, respectively; $a_i(t)>0$ and $b_j(t)>0$ represent the rate with which the $i$th neuron from $F_X$-layer and the $j$th neuron from $F_Y$-layer will reset their potential to the resting state in isolation when disconnected from the networks and external inputs, respectively; $\tau_{ij}$, $\sigma_{ijl}$, $\upsilon_{ijl}$, and $\hat{\tau}_{ij}$, $\hat{\sigma}_{ijl}$, $\hat{\upsilon}_{ijl}$ represent the axonal signal transmission delays; $I_i(t)$ and $J_j(t)$ are the external inputs on the neurons. Here, $\Delta x_i(t_k)=x_i(t_k^+)-x_i(t_k^-)$ and $\Delta y_j(t_k)=y_j(t_k^+)-y_j(t_k^-)$ are the impulses at moments $t_k$ and $t_10$, and $c_i(t)$ and $d_j(t)$ are regressive. And assume that $t-\tau_{ij}(t)$, $t-\sigma_{ijl}(t)$, $t-\upsilon_{ijl}(t)$ $t-\hat{\tau}_{ji}(t)$, $t-\hat{\sigma}_{jir}(t)$ and $t-\hat{\upsilon}_{jir}(t)$ belong to $\mathbb{T}$ for $t\in\mathbb{T}$. \item[(H2)] There exist positive constants $M_j,N_j,\hat{M}_i,\hat{N}_i$, such that $|f_j(x)|\leq M_j$, $|g_j(x)|\leq N_j$, $|p_i(x)|\leq \hat{M}_i$, $|q_i(x)|\leq \hat{N}_i$, for $i=1,2,\dots,n$, $j=1,2,\dots,m$, $x\in\mathbb{R}$. \item[(H3)] Functions $f_j(u),g_j(u),p_i(u),q_i(u)$ satisfy the Lipschitz condition; that is, there exist constants $L_j,H_j,\\\hat{L}_i,\hat{H}_i>0$ such that $|f_j(u_1)-f_j(u_2)|\leq L_j|u_1-u_2|$, $|g_j(u_1)-g_j(u_2)|\leq H_j|u_1-u_2|$, $|p_i(u_1)-p_i(u_2)|\leq \hat{L}_i|u_1-u_2|$, $|q_i(u_1)-q_i(u_2)|\leq \hat{H}_i|u_1-u_2|$ for any $u_1,u_2\in\mathbb{R}$, for $i=1,2,\dots,n$, $j=1,2,\dots,m$. \item[(H4)] There exists a positive integer $q$ such that for $k=1,2,\dots$, $i=1,2,\dots,n$, $j=1,2,\dots,m$, $\{t_k, k=1,2,\dots\}\cap[0,\omega]={t_1,t_2,\dots,t_q}$, $t_{k+q}=t_k+\omega$, $\alpha_{i,k+q}(\cdot)=\alpha_{ik}(\cdot)$, $\beta_{j,k+q}(\cdot)=\beta_{jk}(\cdot)$. \end{itemize} For convenience, we shall use the following notations. $$ \bar{f}=\frac{1}{\omega}\int_{\bar{k}}^{\bar{k}+\omega} f(t)dt,\quad f^+=\max_{t\in[\bar{k},\bar{k}+\omega]\cap\mathbb{T}}|f(t)|, \quad f^-=\min_{t\in[\bar{k},\bar{k}+\omega]\cap\mathbb{T}}|f(t)|, $$ where $\bar{k}=\min\left\{[0,+\infty)\cap\mathbb{T}\right\}$, $f(t)$ is an $\omega$-periodic function. \section{Preliminaries} Some preliminary definitions and theorems on time scales can be found in \cite{10,11}, which are excellent references for the calculus of time scales. We will recall some basic definitions and lemmas which are used in what follows. Let $\mathbb{T}$ be a nonempty closed subset (time scale) of $\mathbb{R}$. The forward and backward jump operators $\sigma,\rho:\mathbb{T}\to\mathbb{T}$ and the graininess $\mu:\mathbb{T}:\mathbb{T}\to \mathbb{R}^+$ are defined by $$ \sigma(t)=\inf\{s\in\mathbb{T}: s>t\},\quad \rho(t)=\sup\{s\in\mathbb{T}: s\inf\mathbb{T}$ and $\rho(t)=t$, left-scattered if left-scattered if $\rho(t)t$. If $\mathbb{T}$ has a left-scattered maximum $m$, then $\mathbb{T}^k=\mathbb{T}\backslash\{m\}$; otherwise $\mathbb{T}^k=\mathbb{T}$. If $\mathbb{T}$ has a right-scattered minimum $m$, then $\mathbb{T}_k=\mathbb{T}\backslash\{m\}$; otherwise $\mathbb{T}_k=\mathbb{T}$. A function $f:\mathbb{T}\to\mathbb{R}$ is right-dense continuous provided that it is continuous at right-dense point in $\mathbb{T}$ and its left-side limits exist at left-dense points in $\mathbb{T}$. If $f$ is continuous at each right-dense point and each left-dense point, then $f$ is said to be continuous function on $\mathbb{T}$. For $y:\mathbb{T}\to\mathbb{R}$ and $t\in\mathbb{T}^k$, we define the delta derivative of y(t), $y^\Delta(t)$ to be the number (if it exists) with the property that for a given $\varepsilon>0$, there exists a neighborhood $U$ of $t$ such that $$ |[y(\sigma(t))-y(s)]-y^\Delta(t)[\sigma(t)-s]|<\varepsilon|\sigma(t)-s|,\quad \forall s\in U. $$ If $y$ is continuous, then $y$ is right-dense continuous, and if $y$ is delta differentiable at $t$, then $y$ is continuous at $t$. A function $r:\mathbb{T}\to\mathbb{R}$ is called regressive if $1+\mu(t)r(t)\neq0$ for all $t\in\mathbb{T}^k$. A function $r$ from $\mathbb{T}$ to $\mathbb{R}$ is positively regressive if $1+\mu(t)r(t)>0$ for every $t\in\mathbb{T}$. Denote $\mathfrak{R}^+$ is the set of positively regressive functions from $\mathbb{T}$ to $\mathbb{R}$, and $\mathbb{T}^+=[0,+\infty)\cap\mathbb{T}$. If $r$ is regressive function, then the generalized exponential function $e_r$ is defined by $$ e_r(t,s)=\exp\Big\{\int_s^t\xi_{\mu(\tau)}(r(\tau))\Delta\tau\Big\} \quad {\rm for}\quad s,t\in\mathbb{T}, $$ with the cylinder transformation \[ \xi_h(z)=\begin{cases} \frac{\log(1+hz)}{h}, &\text{if }h\neq0,\\ z, &\text{if } h=0. \end{cases} \] Let $p,q: \mathbb{T}\to\mathbb{R}$ be two regressive functions, we define $$ p\oplus q:=p+q+\mu pq, \quad \ominus p:=-\frac{p}{1+\mu p},\quad p\ominus q:=p\oplus(\ominus q). $$ The periodic solution $z^\ast(t)=(x^\ast_1(t),\dots,x^\ast_n(t),y^\ast_1(t),\dots,y^\ast_m(t))^T$ of system \eqref{e1.1} is said to be exponentially stable if there exists a positive constant $\vartheta$ such that for every $\varrho\in\mathbb{T}$, there exist $N=N(\varrho)>1$ such that the solution $z(t)=(x_1(t),\dots,x_n(t),\\y_1(t),\dots,y_m(t))^T$ of \eqref{e1.1} satisfies \[ \|z(t)-z^\ast(t)\|\leq Ne_{-\vartheta}(t,\varrho) \Big(\sum_{i=1}^n|\phi_{x_i}(\varrho)-x_i^\ast(\varrho)| +\sum_{j=1}^m|\phi_{y_j}(\varrho)-y_j^\ast(\varrho)|\Big), \] where $\varrho\in[-\max\{\theta,\hat{\theta}\},0]\cap\mathbb{T}$. \begin{lemma}[\cite{5}] \label{l2.1} If $f,g\in C(\mathbb{T},\mathbb{R})$, and $f(t)\leq g(t)$ on $[\bar{k},\bar{k}+\omega)$, then \[ \int_{\bar{k}}^{\bar{k}+\omega}f(t)\Delta t\leq\int_{\bar{k}}^{\bar{k}+\omega}g(t)\Delta t. \] \end{lemma} \begin{lemma}[\cite{12}] \label{l2.2} Let $t_1,t_2\in[\bar{k},\bar{k}+\omega]\cap\mathbb{T}$, $t\in\mathbb{T}$. If $f:\mathbb{T}\to\mathbb{R}$ is $\omega$-periodic, then $$ f(t)\leq f(t_1)+\int_{\bar{k}}^{\bar{k}+\omega}|f^\Delta(t)|\Delta t \quad \text{and}\quad f(t)\geq f(t_2)-\int_{\bar{k}}^{\bar{k}+\omega}|f^\Delta(t)|\Delta t. $$ \end{lemma} \begin{lemma}[\cite{13}] \label{l2.3} Let $a,b\in\mathbb{T}$. For rd-continuous functions $f,g:[a,b]\to\mathbb{R}$, one has $$ \Big(\int_a^b|f(t)g(t)|\Delta t\Big)^2\leq \Big(\int_a^b|f(t)|^2\Delta t\Big)\Big(\int_a^b|g(t)|^2\Delta t\Big). $$ \end{lemma} \begin{lemma}[\cite{14}] \label{l2.4} Let $X$ and $Z$ be two Banach spaces and let $L$ be a Fredholm mapping of index zero. Let $\Omega\subset X$ be an open bounded set and let $N:\overline{\Omega}\to Z$ be a continuous operator which is $L$-compact on $\Omega$. Assume that \begin{itemize} \item[(a)] for each $\lambda\in(0,1)$, $x\in\partial\Omega\cap\operatorname{Dom}L$, $Lx\neq\lambda Nx$; \item[(b)] for each $x\in\partial\Omega\cap\ker L$, $QNx\neq0$; \item[(c)] $\deg (JNQx,\Omega\cap\ker L,0)\neq0$, where $JQN: \ker L\to\ker L$. \end{itemize} Then $Lx=Nx$ has at least one solution in $\overline{\Omega}\cap\operatorname{Dom} L$. \end{lemma} \begin{lemma} \label{l2.5} Let $r : \mathbb{T}\to\mathbb{R}$ be right-dense continuous and regressive. Let $a\in\mathbb{T}$ and $y_a\in\mathbb{R}$. The unique solution of the initial value problem \begin{gather*} y^\Delta(t)=r(t)y(t)+h(t), \quad y(a)=y_a,\\ \Delta y(t_k)=y(t_k^+)-y(t_k^-)=\varphi_{k}(y(t_k)),\quad k=1,2,\dots,q, \end{gather*} is $$ y(t)=e_r(t,a)y_a+\int_a^te_r(t,\sigma(s))h(s)\Delta s+\sum_{k : t_k\in[a,t)_\mathbb{T}} e_r(t,t_k)\varphi_{k}(y(t_k)). $$ \end{lemma} \begin{proof} The proof of Lemma \ref{l2.5} is similar to that of \cite[Lemma 2.7]{15}, it is omitted. \end{proof} According to (H1)--(H4) and $\bar{k}=\min\{[0,+\infty)\cap\mathbb{T}\}$, for system \eqref{e1.1}, finding the periodic solutions is equivalent to finding those of the boundary-value problem \begin{equation} \label{e2.1} \begin{gathered} \begin{aligned} x_i^\Delta(t)&= -c_i(t)x_i(t)+\sum_{j=1}^ma_{ij}(t)f_j(y_j(t-\tau_{ij}(t)))\\ &\quad +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}(t)g_j(y_j(t-\sigma_{ijl}(t))) g_l(y_l(t-\upsilon_{ijl}(t)))+I_i(t),\\ &\quad t\in[\bar{k},\bar{k}+\omega],\; t\neq t_k, \end{aligned} \\ \Delta x_i(t_k)= x_i(t_k^+)-x_i(t_k^-)=\alpha_{ik}(x_i(t_k)), x_i(\bar{k})=x_i(\bar{k}+\omega),\\ i=1,2,\dots,n, k=1,2,\dots,q, \\ \begin{aligned} y_j^\Delta(t)&= -d_j(t)y_j(t)+\sum_{i=1}^ne_{ji}(t)p_i(x_i(t-\hat{\tau}_{ji}(t)))\\ &\quad +\sum_{i=1}^n\sum_{r=1}^nh_{jir}(t)q_i(x_i(t-\hat{\sigma}_{jir}(t))) q_r(x_r(t-\hat{\upsilon}_{jir}(t)))+J_j(t),\\ &\quad t\in[\bar{k},\bar{k}+\omega],\; t\neq t_k, \end{aligned}\\ \Delta y_j(t_k)= y_j(t_k^+)-y_j(t_k^-)=\beta_{jk}(y_j(t_k)), y_j(\bar{k})=y_j(\bar{k}+\omega),\\ j=1,2,\dots,m, k=1,2,\dots,q. \end{gathered} \end{equation} To apply Lemma \ref{l2.4} to system \eqref{e2.1}, we first make the following preparations. For any non-negative integer $q$, let $t_q<\omegat_k}C_k- \frac{1}{\omega}\int_{\bar{k}}^{\bar{k}+\omega}\int_{\bar{k}}^tz(s) \Delta s\Delta t-\sum_{k=1}^qC_k. $$ Therefore, $$ QNz=\begin{pmatrix} \begin{pmatrix} \frac{1}{\omega}\int_0^\omega A_i(t)dt-\frac{1}{\omega} \sum_{k=1}^q\alpha_{ik}(x_i(t_k))\\ \frac{1}{\omega}\int_0^\omega B_j(t)dt-\frac{1}{\omega} \sum_{k=1}^q\beta_{jk}(y_j(t_k)) \end{pmatrix} & 0& \cdots & 0 \end{pmatrix} _{(n+m)\times(q+1)}, $$ and then \begin{align*} K_q(I-Q)Nz &= \begin{pmatrix} \int_0^t A_i(t)dt-\sum_{t>t_k}\alpha_{ik}(x_i(t_k))\\ \int_0^t B_j(t)dt-\sum_{t>t_k}\beta_{jk}(y_j(t_k)) \end{pmatrix}_{(n+m)\times1}\\ &\quad- \begin{pmatrix} \frac{1}{\omega}\int_0^\omega \int_0^tA_i(s)\,ds\,dt\\ \frac{1}{\omega}\int_0^\omega \int_0^tB_j(s)\,ds\,dt \end{pmatrix}_{(n+m)\times1}\\ &\quad-\Big(\frac{t-\bar{k}}{\omega}-\frac{1}{\omega^2}\int_{\bar{k}}^{\bar{k}+\omega} (t-\bar{k})\Delta t\Big) \begin{pmatrix} \int_0^\omega A_i(t)dt\\ \int_0^\omega B_j(t)dt \end{pmatrix}_{(n+m)\times1} \\ &\quad -\begin{pmatrix} \sum_{k=1}^q \alpha_{ik}(x_i(t_k))\\ \sum_{k=1}^q \beta_{jk}(y_j(t_k)) \end{pmatrix}_{(n+m)\times1}. \end{align*} Therefore, $QN$ and $K_q(I-Q)N$ are both continuous. Using the Arzela-Ascoli Theorem, it is easy to show that $\overline{K_p(I-Q)N(\overline{\Omega})}$ is relatively compact. Moreover, $QN(\overline{\Omega})$ is bounded. Thus, $N$ is $L-$compact on $\overline{\Omega}$ for any open bounded set $\Omega\subset \mathbb{X}$. The proof is completed. \end{proof} \section{Existence of periodic solutions} In this section, we study the existence of periodic solution of \eqref{e1.1} based on Mawhins' continuation theorem. \begin{theorem} \label{t3.1} Assume that {\rm (H1)--(H4)} hold, then system \eqref{e1.1} has at least one $\omega$-periodic solution. \end{theorem} \begin{proof} Based on the Lemma \ref{l2.6} and Lemma \ref{l2.7}, what we need to do is just to search for an appropriate open, bounded subset $\Omega$ for the application of the continuation theorem. Corresponding to the operator equation $Lz=\lambda Nz$, $\lambda\in(0,1)$, we have \begin{equation} \label{e3.1} \begin{gathered} \begin{aligned} x_i^\Delta(t) &= \lambda\Big\{-c_i(t)x_i(t)+\sum_{j=1}^ma_{ij}(t)f_j(y_j(t-\tau_{ij}(t))) \\ &\quad+\sum_{j=1}^m\sum_{l=1}^mb_{ijl}(t)g_j(y_j(t-\sigma_{ijl}(t))) g_l(y_l(t-\upsilon_{ijl}(t)))+I_i(t)\Big\}, \\ &\quad t\in[\bar{k},\bar{k}+\omega], t\neq t_k, \end{aligned} \\ \Delta x_i(t_k)= x_i(t_k^+)-x_i(t_k^-)=\alpha_{ik}(x_i(t_k)),\quad x_i(\bar{k})=x_i(\bar{k}+\omega),\\ i=1,2,\dots,n,\; k=1,2,\dots,q, \\ \begin{aligned} y_j^\Delta(t) &= \lambda\Big\{-d_j(t)y_j(t)+\sum_{i=1}^ne_{ji}(t)p_i(x_i(t-\hat{\tau}_{ji}(t)))\\ &\quad +\sum_{i=1}^n\sum_{r=1}^nh_{jir}(t)q_i(x_i(t-\hat{\sigma}_{jir}(t))) q_r(x_r(t-\hat{\upsilon}_{jir}(t)))+J_j(t)\Big\},\\ &\quad t\in[\bar{k},\bar{k}+\omega],\; t\neq t_k, \end{aligned} \\ \Delta y_j(t_k)= y_j(t_k^+)-y_j(t_k^-)=\beta_{jk}(y_j(t_k)),\quad y_j(\bar{k})=y_j(\bar{k}+\omega),\\ j=1,2,\dots,m,\; k=1,2,\dots,q. \end{gathered} \end{equation} For the sake of convenience, we define $$ \|f\|_2=\Big(\int_{\bar{k}}^{\bar{k}+\omega}|f(t)|^2\Delta t\Big)^{1/2}, \quad \text{for } f\in(\mathbb{T},\mathbb{R}). $$ Suppose that $(x_1(t),x_2(t),\dots,x_n(t),y_1(t),y_2(t),\dots,y_m(t))^T\in X$ is a solution of \eqref{e3.1} for a certain $\lambda\in(0,1)$. Integrating \eqref{e3.1} over the interval $[\bar{k},\bar{k}+\omega]$, we obtain \begin{gather*} \int_{\bar{k}}^{\bar{k}+\omega}A_i(t)\Delta t+\sum_{k=1}^q\alpha_{ik}(x_i(t_k))=0, \quad i=1,2,\dots,n,\\ \int_{\bar{k}}^{\bar{k}+\omega}B_j(t)\Delta t+\sum_{k=1}^q\beta_{jk}(y_j(t_k))=0, \quad j=1,2,\dots,m. \end{gather*} Hence \begin{equation} \label{e3.2} \begin{split} &\int_{\bar{k}}^{\bar{k}+\omega}c_i(s)x_i(s)\Delta s \\ &= \int_{\overline{k}}^{\overline{k}+\omega} \Big(\sum_{j=1}^ma_{ij}(t)f_j(y_j(t-\tau_{ij}(t)))\\ &\quad +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}(t)g_j(y_j(t-\sigma_{ijl}(t))) g_l(y_l(t-\upsilon_{ijl}(t)))+I_i(t)\Big)\Delta t\\ &\quad +\sum_{k=1}^q\alpha_{ik}(x_i(t_k)), \end{split} \end{equation} \begin{equation} \label{e3.3} \begin{split} &\int_{\bar{k}}^{\bar{k}+\omega}d_j(s)y_j(s)\Delta s\\ &= \int_{\overline{k}}^{\overline{k}+\omega} \Big(\sum_{i=1}^ne_{ji}(t)p_i(x_i(t-\hat{\tau}_{ji}(t))) \\ &\quad +\sum_{i=1}^n\sum_{r=1}^nh_{jir}(t) q_i(x_i(t-\hat{\sigma}_{jir}(t)))q_r(x_r(t-\hat{\upsilon}_{jir}(t)))+J_j(t)\Big)\Delta t\\ &\quad+\sum_{k=1}^q\beta_{jk}(y_j(t_k)), \end{split} \end{equation} where $i=1,2,\dots,n$, $j=1,2,\dots,m$. Let $\xi_i,\eta_i,\hat{\xi}_j,\hat{\eta}_j (\neq t_k)\in[\bar{k},\bar{k}+\omega] \cap\mathbb{T}$, $k=1,2,\dots,q$, such that $x_i(\xi_i)=\inf_{t\in[\bar{k},\bar{k}+\omega]\cap\mathbb{T}}x_i(t)$, $x_i(\eta_i)=\sup_{t\in[\bar{k},\bar{k}+\omega]\cap\mathbb{T}}x_i(t)$, $y_j(\hat{\xi}_j)=\inf_{t\in[\bar{k},\bar{k}+\omega]\cap\mathbb{T}}y_j(t)$, $y_j(\hat{\eta}_j)=\sup_{t\in[\bar{k},\bar{k}+\omega]\cap\mathbb{T}}y_j(t)$, $i=1,2,\dots,n$, $j=1,2,\dots,m$. Then by \eqref{e3.2} and the Lemma \ref{l2.1}, then we have \begin{align*} \omega\bar{c}_ix_i(\xi_i) &\leq \int_{\bar{k}}^{\bar{k}+\omega}\Big|\sum_{j=1}^ma_{ij}(t)f_j(y_j(t-\tau_{ij}(t)))\\ &\quad +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}(t)g_j(y_j(t-\sigma_{ijl}(t))) g_l(y_l(t-\upsilon_{ijl}(t)))+I_i(t)\Big|\Delta t\\ &\quad+\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))|\\ &\leq \int_{\bar{k}}^{\bar{k}+\omega} \sum_{j=1}^m|a_{ij}(t)||f_j(y_j(t-\tau_{ij}(t)))|\Delta t\\ &\quad+\int_{\bar{k}}^{\bar{k}+\omega}\sum_{j=1}^m \sum_{l=1}^m|b_{ijl}(t)||g_j(y_j(t-\sigma_{ijl}(t)))|| g_l(y_l(t-\upsilon_{ijl}(t)))|\Delta t\\ &\quad+\int_{\bar{k}}^{\bar{k}+\omega}|I_i(t)|\Delta t +\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))|\\ &\leq \omega\Big(\sum_{j=1}^ma_{ij}^+M_j+\sum_{j=1}^m \sum_{l=1}^mb_{ijl}^+N_jN_l+I_i^+\Big) +\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))| \end{align*} for $i=1,2,\dots,n$. Hence \begin{equation} \label{e3.4} \begin{split} x_i(\xi_i)&\leq \frac{1}{\bar{c}_i}\Big(\Big(\sum_{j=1}^ma_{ij}^+M_j +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}^+N_jN_l+I_i^+\Big) +\frac{1}{\omega}\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))|\Big)\\ &= B_i, \quad i=1,2,\dots,n. \end{split} \end{equation} Similarly, by \eqref{e3.3} and Lemma \ref{l2.1}, we obtain \begin{equation} \label{e3.5} \begin{split} y_j(\hat{\xi}_j)&\leq \frac{1}{\bar{d}_j}\Big(\Big(\sum_{i=1}^ne_{ji}^+\hat{M}_i +\sum_{i=1}^n\sum_{r=1}^nh_{jir}^+\hat{N}_i\hat{N}_r+J_j^+\Big) +\frac{1}{\omega}\sum_{k=1}^q|\beta_{jk}(y_j(t_k))|\Big)\\ &= \hat{B}_j, \quad j=1,2,\dots,m. \end{split} \end{equation} By \eqref{e3.2}, we have \begin{align*} \omega\bar{c}_ix_i(\eta_i) &\geq -\int_{\bar{k}}^{\bar{k}+\omega} \Big|\sum_{j=1}^ma_{ij}(t)f_j(y_j(t-\tau_{ij}(t)))\\ &\quad -\sum_{j=1}^m\sum_{l=1}^mb_{ijl}(t) g_j(y_j(t-\sigma_{ijl}(t))) g_l(y_l(t-\upsilon_{ijl}(t)))\\ &\quad +I_i(t)\Big|\Delta t -\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))|\\ &\geq -\int_{\bar{k}}^{\bar{k}+\omega}\sum_{j=1}^m|a_{ij}(t)||f_j(y_j(t-\tau_{ij}(t)))|\Delta t\\ &\quad -\int_{\bar{k}}^{\bar{k}+\omega}\sum_{j=1}^m\sum_{l=1}^m|b_{ijl}(t)||g_j(y_j(t-\sigma_{ijl}(t)))||g_l(y_l(t-\upsilon_{ijl}(t)))|\Delta t\\ &\quad -\int_{\bar{k}}^{\bar{k}+\omega}|I_i(t)|\Delta t-\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))|\\ &\geq -\omega\Big(\sum_{j=1}^ma_{ij}^+M_j +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}^+N_jN_l+I_i^+\Big) -\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))| \end{align*} for $i=1,2,\dots,n$. Hence \begin{equation} \label{e3.6} \begin{split} x_i(\eta_i)&\geq -\frac{1}{\bar{c}_i}\Big(\Big(\sum_{j=1}^ma_{ij}^+M_j +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}^+N_jN_l+I_i^+\Big) +\frac{1}{\omega}\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))|\Big)\\ &= -B_i, \quad i=1,2,\dots,n. \end{split} \end{equation} Similarly, by \eqref{e3.3}, we obtain \begin{equation} \label{e3.7} \begin{split} y_j(\hat{\eta}_j) &\geq -\frac{1}{\bar{d}_j}\Big(\Big(\sum_{i=1}^ne_{ji}^+\hat{M}_i +\sum_{i=1}^n\sum_{r=1}^nh_{jir}^+\hat{N}_i\hat{N}_r+J_j^+\Big) +\frac{1}{\omega}\sum_{k=1}^q|\beta_{jk}(y_j(t_k))|\Big)\\ &= -\hat{B}_j, \quad j=1,2,\dots,m. \end{split} \end{equation} Set $t_0=t_0^+=\bar{k}$, $t_{q+1}=\bar{k}+\omega$. From \eqref{e3.4}, \eqref{e3.6} and Lemma \ref{l2.3}, we have \begin{align} &\int_{\bar{k}}^{\bar{k}+\omega}|x_i^\Delta(t)|\Delta t \nonumber\\ &=\sum_{k=1}^q\int_{t_{k-1}^+}^{t_k}|x^\Delta(t)|\Delta t +\sum_{k=1}^q|x_i(t_k^+)-x_i(t_k)| \nonumber\\ &\leq \int_{\bar{k}}^{\bar{k}+\omega}|c_i(t)||x_i(t)|\Delta t +\int_{\bar{k}}^{\bar{k}+\omega}\sum_{j=1}^m|a_{ij}(t)||f_j(y_j(t-\tau_{ij}(t)))|\Delta t \nonumber\\ &\quad+\int_{\bar{k}}^{\bar{k}+\omega} \sum_{j=1}^m\sum_{l=1}^m|b_{ijl}(t)||g_j(y_j(t-\sigma_{ijl}(t)))|| g_l(y_l(t-\upsilon_{ijl}(t)))|\Delta t \nonumber\\ &\quad+\int_{\bar{k}}^{\bar{k}+\omega}|I_i(t)|\Delta t+\sum_{k=1}^q|e_{ik}(x_i(t_k))| \nonumber\\ &\leq \Big(\int_{\bar{k}}^{\bar{k}+\omega}|c_i(t)|^2\Delta t\Big)^{1/2} \Big(\int_{\bar{k}}^{\bar{k}+\omega}|x_i(t)|^2\Delta t\Big)^{1/2} \label{e3.8} \\ &\quad+\sum_{j=1}^m\Big(\int_{\bar{k}}^{\bar{k}+\omega}|a_{ij}(t)|^2\Delta t\Big)^{1/2} \Big(\int_{\bar{k}}^{\bar{k}+\omega}|f_j(y_j(t-\tau_{ij}(t)))|^2\Delta t\Big)^{1/2} \nonumber\\ &\quad+\sum_{j=1}^m\sum_{l=1}^mb_{ijl}^+\Big(\int_{\bar{k}}^{\bar{k}+\omega} |g_j(y_j(t-\sigma_{ijl}(t)))|^2\Delta t\Big)^{1/2} \nonumber \\ &\quad \times\Big(\int_{\bar{k}}^{\bar{k}+\omega}|g_l(y_l(t-\upsilon_{ijl}(t)))|^2 \Delta t\Big)^{1/2} +I_i^+\omega+\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))| \nonumber\\ &\leq \sqrt{\omega}c_i^+\|x_i\|_2+\sum_{j=1}^m\omega a_{ij}^+M_j +\sum_{j=1}^m\sum_{l=1}^m\omega b_{ijl}^+N_jN_l+I_i^+\omega +\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))|. \nonumber \end{align} Similarly, from \eqref{e3.5} and \eqref{e3.7}, and the Lemma \ref{l2.3}, we obtain \begin{equation} \label{e3.9} \begin{split} \int_{\bar{k}}^{\bar{k}+\omega}|y_j^\Delta(t)|\Delta t &\leq \sqrt{\omega}d_j^+\|y_j\|_2+\sum_{i=1}^n\omega e_{ji}^+\hat{M}_i +\sum_{i=1}^n\sum_{r=1}^n\omega b_{jir}^+\hat{N}_i\hat{N}_r\\ &\quad +J_j^+\omega+\sum_{k=1}^q|\beta_{jk}(y_j(t_k))|. \end{split} \end{equation} From Lemma \ref{l2.5} and \ref{e3.1}, for $i=1,2,\dots,n$, $j=1,2,\dots,m$, we obtain \begin{align*} x_i(t)&= e_{-\lambda c_i(t)}(t,\bar{k})x_i(\bar{k})+ \int_{\bar{k}}^t\lambda e_{-\lambda c_i(t)}(t,\sigma(s)) \Big(\sum_{j=1}^ma_{ij}(s)f_j(y_j(s-\tau_{ij}(s)))\\ &\quad+\sum_{j=1}^m\sum_{l=1}^mb_{ijl}(s)g_j(y_j(s-\sigma_{ijl}(s))) g_l(y_l(s-\upsilon_{ijl}(s)))+I_i(s)\Big)\Delta s\\ &\quad+\sum_{k : t_k\in[\bar{k},t)_\mathbb{T}}e_{-\lambda c_i(t)}(t,t_k) \alpha_{ik}(x(t_k)), \end{align*} \begin{align*} y_j(t)&= e_{-\lambda d_j(t)}(t,\bar{k})y_j(\bar{k})+ \int_{\bar{k}}^t\lambda e_{-\lambda d_j(t)}(t,\sigma(s)) \Big(\sum_{i=1}^ne_{ji}(s)p_i(x_i(s-\hat{\tau}_{ji}(s))) \\ &\quad+\sum_{i=1}^n\sum_{r=1}^nh_{jir}(s)q_r(x_i(s-\hat{\sigma}_{jir}(s))) q_r(x_r(s-\hat{\upsilon}_{jir}(s)))+J_j(s)\Big)\Delta s\\ &\quad+\sum_{k : t_k\in[\bar{k},t)_\mathbb{T}}e_{-\lambda d_j(t)}(t,t_k) \beta_{jk}(y(t_k)). \end{align*} Hence \begin{align*} |x_i(t)| &\leq |x_i(\bar{k})|+\sum_{j=1}^m\int_{\bar{k}}^{\bar{k}+\omega} |a_{ij}(s)||f_j(y_j(s-\tau_{ij}(s)))|\Delta s\\ &\quad+\sum_{j=1}^m\sum_{l=1}^m\int_{\bar{k}}^{\bar{k}+\omega} |b_{ijl}(s)||g_j(y_j(s-\sigma_{ijl}(s)))||g_l(y_l(s-\upsilon_{ijl}(s)))|\Delta s\\ &\quad+\int_{\bar{k}}^{\bar{k}+\omega}|I_i(s)|\Delta s+\sum_{k : t_k\in[\bar{k},t)_\mathbb{T}}|\alpha_{ik}(x(t_k))|\\ &\leq |x_i(\bar{k})|+\sum_{j=1}^m\bar{a}_{ij}N_j\omega+ \sum_{j=1}^m\sum_{l=1}^m\bar{b}_{ijl}N_jN_l\omega+\bar{I}_i\omega +\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))|\\ &= u_i,\\ |y_j(t)|&\leq |y_j(\bar{k})|+\sum_{i=1}^n\bar{e}_{ji}\hat{N}_i\omega+ \sum_{i=1}^n\sum_{r=1}^n\bar{h}_{jir}\hat{N}_i\hat{N}_r\omega+\bar{J}_j\omega +\sum_{k=1}^q|\beta_{jk}(y_j(t_k))|\\ &= \hat{u}_j, \end{align*} where $i=1,2,\dots,n$, $j=1,2,\dots,m$; that is, \begin{equation}\label{e3.10} \begin{gathered} \|x_i\|_2=\Big(\int_{\bar{k}}^{\bar{k}+\omega}|x_i(t)|^2\Delta t\Big)^{1/2} \leq u_i\sqrt{\omega},\\ \|y_j\|_2=\Big(\int_{\bar{k}}^{\bar{k}+\omega}|y_j(t)|^2\Delta t\Big)^{1/2} \leq \hat{u}_j\sqrt{\omega}. \end{gathered} \end{equation} Substituting \eqref{e3.10} in \eqref{e3.8} and \eqref{e3.9}, we obtain \begin{equation} \label{e3.11} \begin{split} \int_{\bar{k}}^{\bar{k}+\omega}|x_i^\Delta(t)|\Delta t &\leq \omega c_i^+u_i+\sum_{j=1}^m\omega a_{ij}^+M_j +\sum_{j=1}^m\sum_{l=1}^m\omega b_{ijl}^+N_jN_l\\ &\quad+I_i^+\omega+\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))|, \quad i=1,2,\dots,n, \end{split} \end{equation} and \begin{equation} \label{e3.12} \begin{split} \int_{\bar{k}}^{\bar{k}+\omega}|y_j^\Delta(t)|\Delta t &\leq \omega d_j^+\hat{u}_j+\sum_{i=1}^n\omega e_{ji}^+\hat{M}_i +\sum_{j=1}^n\sum_{r=1}^n\omega h_{jir}^+\hat{N}_i\hat{N}_r\\ &\quad+J_j^+\omega+\sum_{k=1}^q|\beta_{jk}(y_j(t_k))|, \quad j=1,2,\dots,m. \end{split} \end{equation} From \eqref{e3.6}-\eqref{e3.9} and \eqref{e3.11}-\eqref{e3.12} and Lemma \ref{l2.2}, there exist positive constants $\zeta_i, \hat{\zeta}_j$ $(i=1,2,\dots,n, j=1,2,\dots,m)$ such that for $t\in[\bar{k},\bar{k}+\omega]\cap\mathbb{T}$, $|x_i(t)|\leq\zeta_i$, $|y_j(t)|\leq\hat{\zeta}_j$, $i=1,2,\dots,n$, $j=1,2,\dots,m$. Clearly, $\zeta_i$ and $\hat{\zeta}_j$ ($i=1,2,\dots,n, j=1,2,\dots,m$) are independent of $\lambda$. Denote $H^\ast=\sum_{i=1}^n\zeta_i+\sum_{j=1}^m\hat{\zeta}_j+C$, where $C>0$ is taken sufficiently large such that \begin{align*} &\min_{1\leq i\leq n,1\leq j\leq m}\{\bar{c}_i,\bar{d}_j\}H^*\\ &> n\max\Big(|\bar{I}_i|+\sum_{j=1}^m|\bar{a}_{ij}|M_j +\sum_{j=1}^m\sum_{l=1}^m\bar{b}_{ijl}M_jN_l -\frac{1}{\omega}\sum_{k=1}^q|\alpha_{ik}(x_i(t_k))|\Big)\\ &\quad+m\max\Big(|\bar{J}_j|+\sum_{i=1}^n|\bar{e}_{ji}|\hat{M}_i +\sum_{i=1}^n\sum_{r=1}^n\bar{h}_{jir}\hat{M}_i\hat{N}_r -\frac{1}{\omega}\sum_{k=1}^q|\beta_{jk}(y_j(t_k))|\Big). \end{align*} Now we take $\Omega=\{(x_1(t),\dots,x_n(t),y_1(t),\dots,y_m(t))^T : \|(x_1(t),\dots,x_n(t),y_1(t),\\\dots,y_m(t))^T\|0. \end{align*} Consequently, $QN(x_1,\dots,x_n,y_1,\dots,y_m)^T\neq(0,\dots,0,0,\dots,0)^T$ for $(x_1,\dots,x_n,\\ y_1,\dots,y_m)^T\in\partial\Omega\cap\ker L$. This satisfies condition (b) of Lemma \ref{l2.4}. Define $\Psi : \ker L\times[0,1]\to X$ by \begin{align*} \Psi(x_1,\dots,x_n,y_1,\dots,y_m,\chi) &= -\chi(x_1,\dots,x_n, y_1,\dots,y_m)^T\\ &\quad+(1-\chi)QN(x_1,\dots,x_n,y_1,\dots,y_m)^T. \end{align*} When $(x_1,\dots,x_n,y_1,\dots,y_m)^T\in\partial\Omega\cap\ker L$, $(x_1,\dots,x_n,y_1,\dots,y_m)^T$ is a constant vector in $\mathbb{R}^{n+m}$ with $\sum_{i=1}^n|x_i|+\sum_{j=1}^m|y_j|=H^\ast$, we have $$ \Psi(x_1,\dots,x_n,y_1,\dots,y_m,\chi)\neq(0,\dots,0,0,\dots,0)^T. $$ Therefore, \begin{align*} &\deg \Big(QN(x_1(t),\dots,x_n(t),y_1(t),\dots,y_m(t))^T, \Omega\cap\ker L, (0,\dots,0,0,\dots,0)^T\Big)\\ &= \deg \Big(QN(-x_1(t),\dots,-x_n(t),-y_1(t),\dots,-y_m(t))^T, \Omega\cap\ker L,\\ & (0,\dots,0,0,\dots,0)^T\Big)\neq0. \end{align*} Condition (c) of Lemma \ref{l2.4} is also satisfied. Thus, by Lemma \ref{l2.4} we obtain that $Lx=Nx$ has at least one solution in $\mathbb{X}$. That is, system \eqref{e1.1} has at least one $\omega$-periodic solution. The proof is complete. \end{proof} \section{Global exponential asymptotic stability of periodic solutions} In this section, we will construct some suitable Lyapunov functions to study the global exponential asymptotic stability of the periodic solution of \eqref{e1.1}. \begin{theorem}\label{t4.1} Assume that {\rm (H1)--(H4)} hold. Suppose further that \begin{itemize} \item[(H5)] there exists $n+m$ positive constants $\varepsilon_i>0$ and $\varepsilon_{n+j}>0$, $i=1,2\dots,n$, $j=1,2\dots,m$ such that \begin{gather*} -c_i^-\varepsilon_i+\sum_{j=1}^ma_{ij}^+L_j\varepsilon_{n+j} +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}^+\left(H_jN_l\varepsilon_{n+j} +H_lN_j\varepsilon_{n+l}\right)<0,\quad i=1,2,\dots,n,\\ -d_j^-\varepsilon_{n+j}+\sum_{i=1}^ne_{ji}^+\hat{L}_i\varepsilon_i +\sum_{i=1}^n\sum_{r=1}^nh_{jir}^+\left(\hat{H}_i\hat{N}_r\varepsilon_i +\hat{H}_r\hat{N}_i\varepsilon_r\right)<0,\quad j=1,2,\dots,m; \end{gather*} \item[(H6)] the impulse operators $e_i(x_i(t))$, $i=1,2,\dots,n$ satisfy \begin{gather*} \alpha_i(x_i(t_k))=-\gamma_{ik}(x_i(t_k)-x_i^\ast(t)),\quad 0<\gamma_{ik}<2,\quad i=1,2,\dots,n,\quad k\in\mathbb{Z}^+,\\ \beta_j(y_j(t_k))=-\delta_{jk}(y_j(t_k)-y_j^\ast(t)),\quad 0<\delta_{jk}<2,\quad j=1,2,\dots,m,\quad k\in\mathbb{Z}^+. \end{gather*} \end{itemize} Then the $\omega$-periodic solution of \eqref{e1.1} is globally exponentially stable. \end{theorem} \begin{proof} According to Theorem \ref{t3.1}, we know that \eqref{e1.1} has an $\omega$-periodic solution $z^\ast(t)=(x^\ast_1(t),\dots,x^\ast_n(t),y^\ast_1(t),\\\dots,y^\ast_m(t))^T$. Suppose that $x(t)=(x_1(t),\dots,x_n(t),y_1(t),\dots,y_m(t))^T$ is an arbitrary solution of \eqref{e1.1}. Then it follows from system \eqref{e1.1} that \begin{align*} (x_i(t)-x_i^\ast(t))^\Delta &= -c_i(t)(x_i(t)-x_i^\ast(t))\\ &\quad +\sum_{j=1}^ma_{ij}(t)\Big(f_j(y_j(t-\tau_{ij}(t)))-f_j(y_j^\ast(t-\tau_{ij}(t))) \Big)\\ &\quad +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}(t) \Big(g_j(y_j(t-\sigma_{ijl}(t)))g_l(y_l(t-\upsilon_{ijl}(t)))\\ &\quad -g_j(y_j^\ast(t-\sigma_{ijl}(t)))g_l(y_l^\ast(t-\upsilon_{ijl}(t)))\Big), \end{align*} \begin{align*} (y_j(t)-y_j^\ast(t))^\Delta &= -d_j(t)(y_j(t)-y_j^\ast(t))\\ &\quad +\sum_{i=1}^ne_{ji}(t)\Big(p_i(x_i(t-\hat{\tau}_{ji}(t))) -p_i(x_i^\ast(t-\hat{\tau}_{ji}(t)))\Big)\\ &\quad +\sum_{i=1}^n\sum_{r=1}^nh_{jir}(t) \Big(q_i(x_i(t-\hat{\sigma}_{jir}(t)))q_r(x_r(t-\hat{\upsilon}_{jir}(t))) \\ &\quad -q_i(x_i^\ast(t-\hat{\sigma}_{jir}(t)))q_r(x_r^\ast(t-\hat{\upsilon}_{jir}(t)))\Big), \end{align*} for $i=1,2,\dots,n$, $t>0$, $t\neq t_k$, $k\in\mathbb{Z}^+$, with initial values given by \begin{gather*} x_i(t)=\phi_{x_i}(s),\quad s\in[-\theta,0]\cap\mathbb{T},\quad i=1,2,\dots,n,\\ y_j(t)=\phi_{y_j}(s),\quad s\in[-\hat{\theta},0]\cap\mathbb{T},\quad j=1,2,\dots,m, \end{gather*} where $\theta$ and $\hat{\theta}$ are defined as before. By condition (H3), we obtain \begin{equation} \label{e4.1} \begin{split} &[(x_i(t)-x_i^\ast(t))^\Delta]^+\\ &\leq -c_i^-|x_i(t)-x_i^\ast(t)| +\sum_{j=1}^ma_{ij}^+L_j|y_j(t-\tau_{ij}(t))-y_j^\ast(t-\tau_{ij}(t))|\\ &\quad +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}^+ \Big(H_jN_l|y_j(t-\sigma_{ijl}(t))-y_j^\ast(t-\sigma_{ijl}(t))|\\ &\quad +H_lN_j|y_l(t-\upsilon_{ijl}(t))-y_l^\ast(t-\upsilon_{ijl}(t))|\Big), \end{split} \end{equation} \begin{align*} [(y_j(t)-y_j^\ast(t))^\Delta]^+ &\leq -d_j^-|y_j(t)-y_j^\ast(t)| +\sum_{i=1}^ne_{ji}^+\hat{L}_i|x_i(t-\hat{\tau}_{ji}(t))-x_i^\ast(t-\hat{\tau}_{ji}(t))|\\ &\quad +\sum_{i=1}^n\sum_{r=1}^nh_{jir}^+\Big(\hat{H}_i\hat{N}_r|x_i(t-\hat{\sigma}_{jir} (t))-x_i^\ast(t-\hat{\sigma}_{jir}(t))| \\ &\quad +\hat{H}_r\hat{N}_i|x_r(t-\hat{\upsilon}_{jir}(t)) -x_r^\ast(t-\hat{\upsilon}_{jir}(t))|\Big), \end{align*} for $i=1,2,\dots,n$, $j=1,2,\dots,m$, $t>0$, $t\neq t_k$, $k\in\mathbb{Z}^+$, where $[x_i^\Delta(t)]^+$ and $[y_j^\Delta(t)]^+$ denote the upper right derivative. Also, in view of condition (H6), one has \begin{align*} x_i(t_k+0)-x_i^\ast(t_k+0) &=x_i(t_k)+\alpha_i(x_i(t_k))-x_i^\ast(t_k)-\alpha_i(x_i^\ast(t_k))\\ &=(1-\gamma_{ik})(x_i(t_k)-x_i^\ast(t_k)),\\ y_j(t_k+0)-y_j^\ast(t_k+0)&=y_j(t_k)+\beta_j(y_j(t_k))-y_j^\ast(t_k)-\beta_i(y_j^\ast(t_k))\\ &=(1-\beta_{jk})(y_j(t_k)-y_j^\ast(t_k)), \end{align*} thus \begin{gather*} |x_i(t_k+0)-x_i^\ast(t_k+0)|=|1-\gamma_{ik}||x_i(t_k)-x_i^\ast(t_k)| \leq|x_i(t_k)-x_i^\ast(t_k)|,\\ |y_j(t_k+0)-y_j^\ast(t_k+0)|=|1-\delta_{jk}||y_j(t_k)-y_j^\ast(t_k)| \leq|y_j(t_k)-y_j^\ast(t_k)|, \end{gather*} for $i=1,2,\dots,n$, $j=1,2,\dots,m$, $k\in\mathbb{Z}^+$. According to condition (H5), it can always find a small enough constant $\eta>0$ satisfying $1-\mu(t)\eta>0$ for all $t\in\mathbb{T}$, namely, $-\eta\in\mathfrak{R}^+$ such that \begin{equation} \label{e4.2} \begin{aligned} &(-c_i^-+\eta)\varepsilon_i+\sum_{j=1}^ma_{ij}^+L_je_\eta(t,t-\tau_{ij}(t)) \varepsilon_{n+j} \\ &+\sum_{j=1}^m\sum_{l=1}^mb_{ijl}^+\big(H_jN_l\varepsilon_{n+j}e_\eta(t,t-\sigma_{ijl}(t)) +H_lN_j\varepsilon_{n+l}e_\eta(t,t-\upsilon_{ijl}(t))\big)<0 \end{aligned} \end{equation} for $i=1,2,\dots,n$; \begin{align*} &(-d_j^-+\eta)\varepsilon_{n+j}+\sum_{i=1}^ne_{ji}^+\hat{L}_ie_\eta(t,t-\hat{\tau}_{ji}(t)) \varepsilon_i \\ &+\sum_{i=1}^n\sum_{r=1}^nh_{jir}^+ \big(\hat{H}_i\hat{N}_r\varepsilon_ie_\eta(t,t-\hat{\sigma}_{jir}(t)) +\hat{H}_r\hat{N}_i\varepsilon_re_\eta(t,t-\hat{\upsilon}_{jir}(t))\big)<0 \end{align*} for $j=1,2,\dots,m$. Now we define a Lyapunov function $V=(\varphi_1,\dots,\varphi_n,\psi_1,\dots,\psi_m)^T$, with \begin{gather*} \varphi_i(t)=e_\eta(t,\varrho)|x_i(t)-x_i^\ast(t)|,\quad t\in[-\theta,\infty]\cap\mathbb{T}, i=1,2,\dots,n,\\ \psi_j(t)=e_\eta(t,\varrho)|y_j(t)-y_j^\ast(t)|,\quad t\in[-\hat{\theta},\infty]\cap\mathbb{T},j=1,2,\dots,m, \end{gather*} where $\varrho\in[-\max\{\theta,\hat{\theta}\},0]\cap\mathbb{T}$. In view of \eqref{e4.1}, we obtain \begin{align} &[\varphi_i^\Delta(t)]^+ \nonumber \\ &=\eta e_\eta(t,\varrho)|x_i(t)-x^\ast_i(t)|+e_\eta\sigma(t),\varrho) \operatorname{sign}(x_i(t)-x^\ast_i(t)) \nonumber\\ &\quad\times\Big(-c_i(t)(x_i(t)-x_i^\ast(t)) +\sum_{j=1}^ma_{ij}(t)\big(f_j(y_j(t-\tau_{ij}(t)))-f_j(y_j^\ast(t-\tau_{ij}(t)))\big) \nonumber\\ &\quad +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}(t) \big(g_j(y_j(t-\sigma_{ijl}(t)))g_l(y_l(t-\upsilon_{ijl}(t)))\nonumber\\ &\quad -g_j(y_j^\ast(t-\sigma_{ijl}(t)))g_l(y_l^\ast(t-\upsilon_{ijl}(t)))\big)\Big) \nonumber\\ &\leq\eta e_\eta(t,\varrho)|x_i(t)-x^\ast_i(t)|+e_\eta(\sigma(t),\varrho) \label{e4.3} \\ &\quad \times\Big(-c_i^-|x(t)-x^\ast(t)| +\sum_{j=1}^ma_{ij}^+L_j|y_j(t-\tau_{ij}(t))-y_j^\ast(t-\tau_{ij}(t))| \nonumber\\ &\quad +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}^+ \big(H_jN_l|y_j(t-\sigma_{ijl}(t))-y_j^\ast(t-\sigma_{ijl}(t))| \nonumber\\ &\quad +H_lN_j|y_l(t-\upsilon_{ijl}(t))-y_l^\ast(t-\upsilon_{ijl}(t))|\big)\Big) \nonumber\\ &\leq e_\eta(\sigma(t),\varrho)\Big((-c_i^-+\eta)|x_i(t)-x_i^\ast(t)| +\sum_{j=1}^ma_{ij}^+L_j|y_j(t-\tau_{ij}(t))-y_j^\ast(t-\tau_{ij}(t))| \nonumber\\ &\quad +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}^+ \big(H_jN_l|y_j(t-\sigma_{ijl}(t))-y_j^\ast(t-\sigma_{ijl}(t))| \nonumber\\ &\quad +H_lN_j|y_l(t-\upsilon_{ijl}(t))-y_l^\ast(t-\upsilon_{ijl}(t))|\big)\Big) \nonumber\\ &\leq (1+\mu(t)\eta)\Big((-c_i^-+\eta)\varphi_i(t) +\sum_{j=1}^ma_{ij}^+L_je_\eta(t,t-\tau_{ij}(t))\psi_j(t-\tau_{ij}(t)) \nonumber\\ &\quad +\sum_{j=1}^m\sum_{l=1}^mb_{ijl}^+ \big(H_jN_le_\eta(t,t-\sigma_{ijl}(t))\psi_j(t-\sigma_{ijl}(t)) \nonumber\\ &\quad +H_lN_je_\eta(t,t-\upsilon_{ijl}(t))\psi_l(t-\upsilon_{ijl}(t))\big)\Big), \nonumber \end{align} \begin{equation} \label{e4.4} \begin{split} &[\psi_i^\Delta(t)]^+ \\ &\leq(1+\mu(t)\eta)\Big((-d_j^-+\eta)\psi_j(t) +\sum_{i=1}^ne_{ji}^+\hat{L}_ie_\eta(t,t-\hat{\tau}_{ji}(t)) \varphi_i(t-\hat{\tau}_{ji}(t)) \\ &\quad +\sum_{i=1}^n\sum_{r=1}^nh_{jir}^+ \big(\hat{H}_i\hat{N}_re_\eta(t,t-\hat{\sigma}_{jir}(t)) \varphi_i(t-\hat{\sigma}_{jir}(t)) \\ &\quad +\hat{H}_r\hat{N}_ie_\eta(t,t-\hat{\upsilon}_{jir}(t)) \varphi_r(t-\hat{\upsilon}_{jir}(t))\big)\Big), \end{split} \end{equation} for $i=1,2,\dots,n$, $j=1,2,\dots,m$. Also, \begin{gather*} \varphi_i(t_k+0)=|1-\gamma_{ik}|\varphi_i(t_k)\leq\varphi_i(t_k),\quad i=1,2,\dots,n,\; k\in\mathbb{Z}^+,\\ \psi_j(t_k+0)=|1-\delta_{jk}|\psi_j(t_k)\leq\psi_j(t_k),\quad j=1,2,\dots,m,\; k\in\mathbb{Z}^+. \end{gather*} Let $\varepsilon_M=\max_{1\leq i\leq n,1\leq j\leq m}\{\varepsilon_i,\varepsilon_{n+j}\}$, $\varepsilon_L=\min_{1\leq i\leq n,1\leq j\leq m}\{\varepsilon_i,\varepsilon_{n+j}\}$, $l_0=(1-\varrho)(\sum_{i=1}^n|\phi_{x_i}-x_i^\ast|_0+\sum_{j=1}^m|\phi_{y_j}-y_j^\ast|_0) /{\varepsilon_L}$, where $-\varrho\geq0$ is a constant, $|\phi_{x_i}-x_i^\ast|_0=\sup_{\varrho\in[-\theta,0]\cap\mathbb{T}}|\phi_{x_i} (\varrho)-x_i^\ast(\varrho)|$, $|\phi_{y_j}-y_j^\ast|_0=\sup_{\varrho\in[-\hat{\theta},0] \cap\mathbb{T}}|\phi_{y_j}(\varrho)-y_j^\ast(\varrho)|$. Then \begin{gather*} |\varphi_i(\varrho)|=e_\eta(t,\varrho)|\phi_{x_i}(\varrho)-x_i^\ast(\varrho)| <\varepsilon_il_0, \quad \varrho\in[-\theta,0]\cap\mathbb{T},\; i=1,2,\dots,n,\\ |\psi_i(\varrho)|=e_\eta(t,\varrho)|\phi_{y_j}(\sigma)-y_j^\ast(\varrho)| <\varepsilon_{n+j}l_0, \quad \varrho\in[-\hat{\theta},0]\cap\mathbb{T},\; j=1,2,\dots,m. \end{gather*} In the following, we will prove that $|\varphi_i(t)|<\varepsilon_il_0$, $|\psi_j(t)|<\varepsilon_{n+j}l_0$, for $t>0$, $i=1,2,\dots,n$, $j=1,2,\dots,m$. If it is not true, no loss of generality, then there exist some $i_0$ and $t_1$ $(t_1>0)$ such that $|\varphi_{i_0}(t_1)|=\varepsilon_{i_0}l_0$, $[\varphi_{i_0}^\Delta(t_1)]^+\geq0$ and $|\varphi_i(t)|<\varepsilon_il_0$, $t\in[-\theta,t_1]\cap\mathbb{T}$, $|\psi_j(t)|<\varepsilon_{n+j}l_0$, $t\in[-\hat{\theta},t_1]\cap\mathbb{T}$, for $i=1,2,\dots,n$, $j=1,2,\dots,m$. However, from \eqref{e4.2} and \eqref{e4.3}, we obtain \begin{align*} &[\varphi_{i_0}^\Delta(t_1)]^+\\ &\leq(1+\mu(t_1)\eta)\Big((-c_{i_0}^-+\eta)\varepsilon_{i_0} +\sum_{j=1}^ma_{i_0j}^+L_je_\eta(t_1,t_1-\tau_{{i_0}j}(t_1))\varepsilon_j\\ &\quad +\sum_{j=1}^m\sum_{l=1}^mb_{i_0jl}^+ \big(H_jN_le_\eta(t_1,t_1-\sigma_{i_0jl}(t_1))\varepsilon_j +H_lN_je_\eta(t_1,t_1-\upsilon_{i_0jl}(t_1))\varepsilon_l\big)\Big)l_0\\ &<0, \end{align*} this is a contradiction. So $|\varphi_i(t)|<\varepsilon_il_0$, $|\psi_j(t)|<\varepsilon_{n+j}l_0$, for $t>0$, $i=1,2,\dots,n$, $j=1,2,\dots,m$. That is, \[ e_\eta(t,\varrho)|x_i(t)-x_i^\ast(t)|<\varepsilon_il_0 \leq\frac{\varepsilon_i}{\varepsilon_L}(1-\varrho) \Big(\sum_{i=1}^n|\phi_{x_i}-x_i^\ast|_0+\sum_{j=1}^m|\phi_{y_j}-y_j^\ast|_0\Big) \] for $t>0$, $i=1,2,\dots,n$, and \[ e_\eta(t,\varrho)|y_j(t)-y_j^\ast(t)|<\varepsilon_{n+j}l_0 \leq\frac{\varepsilon_{n+j}}{\varepsilon_L} (1-\varrho)\Big(\sum_{i=1}^n|\phi_{x_i}-x_i^\ast|_0+\sum_{j=1}^m|\phi_{y_j}-y_j^\ast|_0 \Big) \] for $t>0$, $j=1,2,\dots,m$, which means that \begin{equation} \label{e4.5} \begin{split} &\sum_{i=1}^n|x_i(t)-x_i^\ast(t)|_0+\sum_{j=1}^m|y_j(t)-y_j^\ast(t)|_0\\ &\leq\frac{\varepsilon_M}{\varepsilon_m}e_{\ominus\eta}(t,\varrho) (1-\varrho)(n+m)\Big(\sum_{i=1}^n|\phi_{x_i}(\varrho)-x_i^\ast(\varrho) |_0\\ &\quad +\sum_{j=1}^m|\phi_{y_j}(\varrho)-y_j^\ast(\varrho)|_0\Big). \end{split} \end{equation} Denote $-\vartheta=\ominus\eta=-\eta/(1+\mu\eta)\in\mathbb{R}$, $N=N(\varrho)=\varepsilon_M/\varepsilon_m(1-\varrho)(n+m)>1$, in view of \eqref{e4.5}, we have \[ \|z(t)-z^\ast(t)\|\leq Ne_{-\vartheta}(t,\varrho) \Big(\sum_{i=1}^n|\phi_{x_i}(\varrho)-x_i^\ast(\varrho)|_0 +\sum_{j=1}^m|\phi_{y_j}(\varrho)-y_j^\ast(\varrho)|_0\Big), \] and we can conclude that the $\omega$-periodic solution of \eqref{e1.1} is globally exponentially stable and this completes the proof. \end{proof} \section{An illustrative example} In this section, we give an example to illustrate the results in this article. Let $\mathbb{T}=\bigcup_{k=0}^\infty[2k,2k+1]$. We will apply our main results to the BAM HHNNs with impulses and delays on time scales \begin{equation} \label{e5.1} \begin{gathered} \begin{aligned} x_i^\Delta(t) &= -c_i(t)x_i(t)+\sum_{j=1}^2a_{ij}(t)f_j(y_j(t-\tau_{ij}(t)))\\ &\quad +\sum_{j=1}^2\sum_{l=1}^2b_{ijl}(t) g_j(y_j(t-\sigma_{ijl}(t)))g_l(y_l(t-\upsilon_{ijl}(t)))+I_i(t),\; t\neq t_k, \end{aligned}\\ \Delta x_i(t_k) = \alpha_{ik}(x_i(t_k))=-\gamma_{ik}(x_i(t_k)-x_i^\ast(t)),\quad i=1,2,\; k=1,2,\dots, \\ \begin{aligned} y_j^\Delta(t) &= -d_j(t)y_j(t)+\sum_{i=1}^2e_{ji}(t)p_i(x_i(t-\hat{\tau}_{ji}(t)))\\ &\quad +\sum_{i=1}^2\sum_{r=1}^2h_{jir}(t)q_i(x_i(t-\hat{\sigma}_{jir}(t))) q_r(x_r(t-\hat{\upsilon}_{jir}(t)))+J_j(t),\; t\neq t_k, \end{aligned} \\ \Delta y_j(t_k)= \beta_{jk}(y_j(t_k))=-\delta_{jk}(y_j(t_k)-y_j^\ast(t)),\quad j=1,2, \quad k=1,2,\dots, \end{gathered} \end{equation} where \begin{gather*} f_1(x)=\sin\big(\frac{1}{\sqrt{2}}x\big),\quad f_2(x)=\sin\big(\frac{1}{2\sqrt{2}}x\big),\quad g_1(x)=\arctan\big(\frac{1}{\sqrt{2}}x\big),\\ g_2(x)=\arctan\big(\frac{1}{2\sqrt{2}}x\big),\quad p_1(x)=\cos\big(\frac{1}{\sqrt{3}}x\big),\quad p_2(x)=\cos\big(\frac{1}{3\sqrt{3}}x\big),\\ q_1(x)=\operatorname{arccot}\big(\frac{1}{\sqrt{3}}x\big),\quad q_2(x)=\operatorname{arccot}\big(\frac{1}{3\sqrt{3}}x\big). \end{gather*} Obviously, $f_j(x),g_j(x) (j=1,2)$, $p_i(x),q_i(x) (i=1,2)$ satisfy (H2) and (H3), and \begin{gather*} M_1=M_2=L_1=L_2=H_1=H_2=1,\quad N_1=N_2=\frac{\pi}{2},\\ \hat{M}_1=\hat{M}_2=\hat{L}_1=\hat{L}_2=\hat{H}_1=\hat{H}_2=1,\quad \hat{N}_1=\hat{N}_2=\pi. \end{gather*} Take \begin{gather*} a_{11}(t)=1+\cos(2\pi t),\quad a_{12}(t)=2+\cos(2\pi t),\quad a_{21}(t)=2+\cos(2\pi t),\\ a_{22}(t)=3+\cos(2\pi t),\quad c_1(t)=20+5\sin(2\pi t),\quad c_2(t)=33+16\sin(2\pi t),\\ I_1(t)=1+\sin(2\pi t),\quad I_2(t)=1+\cos(2\pi t),\quad b_{111}(t)=b_{222}(t)=\frac{1}{4}+\frac{1}{4}\sin(2\pi t),\\ b_{112}(t)=b_{212}(t)=\frac{1}{3}+\frac{1}{3}\cos(2\pi t),\quad b_{121}(t)=b_{221}(t)=\frac{1}{5}+\frac{1}{5}\cos(2\pi t),\\ b_{122}(t)=b_{211}(t)=\frac{1}{6}+\frac{1}{6}\sin(2\pi t),\quad \gamma_{1k}=1+\frac{1}{2}\sin(2+k),\\ \gamma_{2k}=1+\frac{6}{7}\cos(5+k^2), k\in\mathbb{Z}^+,\quad e_{11}(t)=1+\sin(2\pi t),\quad e_{12}(t)=1+2\sin(2\pi t),\\ e_{21}(t)=1+2\cos(2\pi t),\quad e_{22}(t)=3+\sin(2\pi t),\quad d_1(t)=21+6\cos(2\pi t),\\ d_2(t)=31+14\cos(2\pi t),\quad J_1(t)=2+3\sin(2\pi t), J_2(t)=3+2\cos(2\pi t),\\ h_{111}(t)=h_{222}(t)=\frac{1}{8}+\frac{1}{8}\sin(2\pi t),\quad h_{112}(t)=h_{212}(t)=\frac{1}{6}+\frac{1}{6}\cos(2\pi t),\\ h_{121}(t)=h_{221}(t)=\frac{1}{10}+\frac{1}{10}\sin(2\pi t),\quad h_{122}(t)=h_{211}(t)=\frac{1}{12}+\frac{1}{12}\cos(2\pi t),\\ \delta_{1k}=1+\frac{2}{5}\cos(3+k),\quad \delta_{2k}=1+\frac{4}{7}\sin(9+k^2), k\in\mathbb{Z}^+. \end{gather*} One can verify that (H1) is satisfied, and $\omega=1$, $c_1^-=15$, $c_2^-=17$, $a_{11}^+=2$, $a_{12}^+=3$, $a_{21}^+=3$, $a_{22}^+=4$, $b_{111}^+=b_{222}^+=1/2$, $b_{112}^+=b_{212}^+=2/3$, $b_{121}^+=b_{221}^+=2/5$, $b_{122}^+=b_{211}^+=1/3$, $0<\gamma_{ik}<2 (i=1,2)$, $d_1^-=15$, $d_2^-=17$, $e_{11}^+=2$, $e_{12}^+=3$, $e_{21}^+=3$, $e_{22}^+=4$, $h_{111}^+=h_{222}^+=1/4$, $h_{112}^+=h_{212}^+=1/3$, $h_{121}^+=h_{221}^+=1/5$, $h_{122}^+=h_{211}^+=1/6$, $0<\delta_{ik}<2 (i=1,2)$, so, if we take $\varepsilon_1=\varepsilon_2=\varepsilon_3=\varepsilon_4=1$, we can obtain \begin{gather*} \begin{aligned} &-c_1^-\varepsilon_1+\sum_{j=1}^2a_{1j}^+L_j\varepsilon_{2+j} +\sum_{j=1}^2\sum_{l=1}^2b_{1jl}^+\big(H_jN_l\varepsilon_{2+j} +H_lN_j\varepsilon_{2+l}\big)\\ & =-15+5+\frac{19}{10}\pi<0, \end{aligned}\\ \begin{aligned} &-c_2^-\varepsilon_2+\sum_{j=1}^2a_{2j}^+L_j\varepsilon_{2+j} +\sum_{j=1}^2\sum_{l=1}^2b_{2jl}^+\big(H_jN_l\varepsilon_{2+j} +H_lN_j\varepsilon_{2+l}\big)\\ &=-17+7+\frac{19}{10}\pi<0, \end{aligned}\\ -d_3^-\varepsilon_3+\sum_{i=1}^2e_{1i}^+\hat{L}_i\varepsilon_i +\sum_{i=1}^2\sum_{r=1}^2h_{1ir}^+\big(\hat{H}_i\hat{N}_r\varepsilon_i +\hat{H}_r\hat{N}_i\varepsilon_r\big)=-15+5+\frac{19}{10}\pi<0,\\ -d_4^-\varepsilon_4+\sum_{i=1}^2e_{2i}^+\hat{L}_i\varepsilon_i +\sum_{i=1}^2\sum_{r=1}^2h_{2ir}^+\big(\hat{H}_i\hat{N}_r\varepsilon_i +\hat{H}_r\hat{N}_i\varepsilon_r\big)=-17+7+\frac{19}{10}\pi<0. \end{gather*} Conditions (H5) and (H6) are satisfied. 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