\documentclass[reqno]{amsart} \usepackage{hyperref} \usepackage{graphicx} \AtBeginDocument{{\noindent\small \emph{Electronic Journal of Differential Equations}, Vol. 2010(2010), No. 59, pp. 1--9.\newline ISSN: 1072-6691. URL: http://ejde.math.txstate.edu or http://ejde.math.unt.edu \newline ftp ejde.math.txstate.edu} \thanks{\copyright 2010 Texas State University - San Marcos.} \vspace{9mm}} \begin{document} \title[\hfilneg EJDE-2010/59\hfil Anti-periodic solutions] {Anti-periodic solutions for high-order cellular neural networks with time-varying delays} \author[Z. Huang, L. Peng, M. Xu\hfil EJDE-2010/59\hfilneg] {Zuda Huang, Lequn Peng, Min Xu} % in alphabetical order \address{Department of Mathematics, Hunan University of Arts and Science, Changde, Hunan 415000, China} \email[Z. Huang]{yitang1972@yahoo.com.cn} \email[L. Peng]{penglq1956@yahoo.com.cn} \email[M. Xu]{xumincd2010@yahoo.com.cn} \thanks{Submitted November 2, 2009. Published april 28, 2010.} \thanks{Supported by the Key Project of Chinese Ministry of Education (No. 2010 151), \hfill\break\indent the grants 06JJ2063, 07JJ6001 from the Scientific Research Fund of Hunan \hfill\break\indent Provincial Natural Science Foundation, and 08C616, 09B072 from the Scientific Research \hfill\break\indent Fund of Hunan Provincial Education Department of China} \subjclass[2000]{34C25, 34K13, 34K25} \keywords{High-order cellular neural networks; anti-periodic; \hfill\break\indent exponential stability; time-varying delays.} \begin{abstract} In this article, we study anti-periodic solutions for high-order cellular neural networks with time-varying delays. Sufficient conditions for the existence and exponential stability of anti-periodic solutions are presented. \end{abstract} \maketitle \numberwithin{equation}{section} \newtheorem{theorem}{Theorem}[section] \newtheorem{lemma}[theorem]{Lemma} \newtheorem{definition}[theorem]{Definition} \newtheorem{remark}[theorem]{Remark} \section{Introduction} In recent years, high-order cellular neural networks (HCNNs) have attracted attention due to their wide range of applications in fields such as signal and image processing, pattern recognition, optimization, and many other subjects. There have been many results on the problem of global stability of equilibrium points and periodic solutions of HCNNs in the literature (see \cite{c1,c2,l2,w1,w2,x1,x2,z1}). However, there are only a few references on the problem of existence and stability of anti-periodic solutions. However, the existence of anti-periodic solutions is important in nonlinear differential equation (see \cite{a1,a2,l1,o1,p1}). Thus, it is worth while to investigate the existence and stability of anti-periodic solutions for HCNNs. In this article, we study the anti-periodic solution of the high-order cellular neural network medelled by \begin{equation} \label{e1.1} \begin{aligned} x'_{i}(t) &= -c_{i}(t)x_{i}(t)+ \sum_{j=1}^{n}a_{ij}(t)f_{j}(x_{j}(t-\widetilde{\tau}_{j}(t)))\\ &\quad+\sum_{j=1}^{n}\sum_{k=1}^{n}b_{ijk}(t)g_{j}(x_{j} (t-\tau_{j}(t)))g_{k}(x_{k}(t-\tau_{k}(t)))+u_{i}(t), \end{aligned} \end{equation} where $i=1, 2, \dots, n$; $c_{i},a_{ij},b_{ijk},f_{j}, g_{j}, u_{i}$ are continuous functions on $\mathbb{R}$; $x=(x_{1}, x_{2}, \dots, x_{n})^{T}\in \mathbb{R}^n$ is the state vector; $c_{i}$ is a positive parameter; $a_{ij}$ and $b_{ijk}$ are the first and second order connection weights of the neural networks, respectively; $f_{j}$ and $ g_{j}$ are the activation functions; $u_{i}$ is an external input to the $i$th neuron; $\widetilde{\tau}_{j}(t)$ and $\tau_{j}(t)$ are the time-varying delay that satisfy $0\leq\widetilde{\tau}_{j}(t)\leq\tau $ and $0\leq\tau_{j}(t)\leq\tau $ ($\tau$ is a constant). The initial conditions are \begin{equation} \label{e1.2} x_{i}(t)=\varphi_{i}(t),\quad t\in [-\tau,0],\;i=1, 2, \dots, n, \end{equation} where $\varphi(\cdot)=[\varphi_{1}(\cdot),\varphi_{2}(\cdot), \dots,\varphi_{n}(\cdot)]\in C([-\tau,0],\mathbb{R}^n)$ and $C([-\tau,0],\mathbb{R}^n)$ denotes the set of continuous functions. The rest of this article is organized as follows. In Section 2, we give some notations and preliminary knowledge. In Section 3, we present our main results. In Section 4, we present an example to illustrate the effectiveness of our results. Finally, we give the conclusions in Section 5. \section{Preliminary Results} A continuous function $h:\mathbb{R}\to \mathbb{R}$ is said to be $T$-anti-periodic on $\mathbb{R}$, if $$ h(t+T)=-h(t)\quad \text{for all } t\in \mathbb{R}. $$ We consider \eqref{e1.1} under the following assumptions: For $i, j=1, 2, \dots, n$, it will be assumed that \begin{equation} \begin{gathered} c_{i}(t+T)=c_{i}(t),\quad \tau_{i}(t+T)=\tau_{i}(t), \quad a_{ij}(t+T)f_{j}(v)=-a_{ij}(t)f_{j}(-v),\\ \widetilde{\tau}_{j}(t+T)=\widetilde{\tau}_{j}(t), \quad b_{ijk}(t+T)=-b_{ijk}(t), \quad u_{i}(t+T)=-u_{i}(t),\quad \forall t,v\in \mathbb{R}. \end{gathered}\label{e2.1} \end{equation} and \begin{equation} \overline{u}=\max_{1\leq i\leq n}\sup_{t\in \mathbb{R}}|u_{i}(t)|. \label{e2.2} \end{equation} Also we will use the assumptions. \begin{itemize} \item[(H1)] For $j=1, 2, \dots, n $, there exist $\overline{g_{j}}>0$ such that $|g_{j}(u)|\leq\overline{g_{j}}$ for all $u \in \mathbb{R}$; \item[(H2)] for $j=1, 2, \dots, n $, there exist $L_{j}>0$ and $M_{j}>0$ such that \begin{gather*} |f_{j}(u )-f_{j}(v )| \leq L_{j}|u -v |,\quad |g_{j}(u )-g_{j}(v )| \leq M_{j}|u -v |,\\ f_{j}(0)=0,\quad g_{j}(0)=0,\quad \forall u , v \in \mathbb{R}. \end{gather*} \item[(H3)] There exist constants $\eta>0, \lambda>0$ and $\xi_{i}>0$, $i=1, 2, \dots, n$, such that for all $t>0$, $$ [\lambda-c_{i}(t)]\xi_{i}+\Big[\sum_{j=1}^{n}|a_{ij}(t)|L_{j}\xi_{j} +\sum_{j=1}^{n}\sum_{k=1}^{n} |b_{ijk}(t)|(\overline{g_{k}}M_{j}\xi_{j} +\overline{g_{j}}M_{k}\xi_{k})\Big]e^{\lambda \tau}<-\eta<0. $$ \end{itemize} \begin{definition} \label{def2.1} \rm Let $x^{*}(t)=\big(x^{*}_{1}(t), x^{*}_{2}(t),\dots,x^{*}_{n}(t)\big)^{T} $ be an anti-periodic solution of \eqref{e1.1} with initial value $\varphi^{*}=(\varphi^{*}_{1}(t), \varphi^{*}_{2}(t), \dots, \varphi^{*}_{n}(t))^{T} $. If there exist constants $\lambda>0$ and $M_{\varphi} >1$ such that for every solution $x(t)=(x_{1}(t), x_{2}(t),\dots,x_{n}(t))^{T} $ of \eqref{e1.1} with an initial value $ \varphi=(\varphi_{1}(t), \varphi_{2}(t), \dots, \varphi_{n}(t))^{T}$, with $$ |x_{i}(t)-x^{*}_{i}(t)|\leq M_{\varphi} \|\varphi-\varphi^{*}\|e^{-\lambda t},\quad \forall t>0, \; i=1, 2, \dots, n, $$ where $$ \|\varphi-\varphi^{*}\|=\sup_{-\tau\leq s\leq0} \max_{1\leq i\leq n}|\varphi_{i}(s)-\varphi_{i}^{*}(s)|. $$ Then $x^{*}(t)$ is said to be globally exponentially stable. \end{definition} Next, we present two important lemmas, to be used for proving our main results in Section 3. \begin{lemma} \label{lem2.1} Let {\rm (H1)--(H3)} hold. Suppose that $\widetilde{x}(t)= (\widetilde{x}_{1}(t), \widetilde{x}_{2}(t),\dots, \widetilde{x}_{n}(t))^{T} $ is a solution of \eqref{e1.1} with initial conditions \begin{equation} \widetilde{x}_{i}(s)=\widetilde{\varphi}_{i}(s), \quad |\widetilde{\varphi}_{i}(s)|<\xi_{i}\frac{\overline{u}+1}{\eta}, \quad s\in [-\tau,0], \; i=1,2,\dots,n.\label{e2.3} \end{equation} Then \begin{equation} |\widetilde{\varphi}_{i}(t)|<\xi_{i}\frac{\overline{u}+1}{\eta}, \quad \text{for all } t\geq 0, \; i=1,2,\dots,n.\label{e2.4} \end{equation} \end{lemma} \begin{proof} Assume, by way of contradiction, assume that \eqref{e2.4} does not hold. Then there must exist $i\in \{1,2,\dots,n \}$ and $\sigma>0$ such that \begin{equation} |\widetilde{x}_{i}(\sigma)| =\xi_{i}\frac{\overline{u}+1}{\eta}, \quad\text{and}\quad |\widetilde{x}_{j}(t)| <\xi_{j}\frac{\overline{u}+1}{\eta} \quad \text{for all } t\in (-\tau, \sigma), \; j=1,2,\dots,n.\label{e2.5} \end{equation} By directly computing the upper left derivative of $|\widetilde{x}_{i}(t)|$. under assumptions (H1)--(H3), and \eqref{e2.5}, we deduce that \begin{equation} \begin{aligned} 0 & \leq D^+(|\widetilde{x}_{i}(\sigma)|) \\ & \leq -c_{i}(\sigma)|\widetilde{x}_{i}(\sigma)|+\sum_{j=1}^{n}|a_{ij}(\sigma)||f_{j}(\widetilde{x}_{j}(\sigma-\widetilde{\tau}_{j}(\sigma)))|\\ &\quad +\sum_{j=1}^{n}\sum_{k=1}^{n}|b_{ijk}(\sigma)||g_{j}(\widetilde{x}_{j}(\sigma-\tau_{j}(\sigma)))|\overline{g_{k}}+|u_{i}(\sigma)|\\ & \leq -c_{i}(\sigma)\xi_{i}\frac{\overline{u}+1}{\eta}+\sum_{j=1}^{n}|a_{ij}(\sigma)|L_{j}|\widetilde{x}_{j}(\sigma-\widetilde{\tau}_{j}(\sigma))|\\ &\quad +\sum_{j=1}^{n}\sum_{k=1}^{n}|b_{ijk}(\sigma)|M_{j}|\widetilde{x}_{j}(\sigma-\tau_{j}(\sigma))|\overline{g_{k}}+\overline{u}\\ & \leq -c_{i}(\sigma)\xi_{i}\frac{\overline{u}+1}{\eta}+\sum_{j=1}^{n}|a_{ij}(\sigma)|L_{j}\xi_{j}\frac{\overline{u}+1}{\eta} +\sum_{j=1}^{n}\sum_{k=1}^{n}|b_{ijk}(\sigma)|M_{j}\xi_{j}\frac{\overline{u}+1}{\eta}\overline{g_{k}}+\overline{u}\\ & = [-c_{i}(\sigma)\xi_{i}+\sum_{j=1}^{n}|a_{ij}(\sigma)|L_{j}\xi_{j} +\sum_{j=1}^{n}\sum_{k=1}^{n}|b_{ijk}(\sigma)|M_{j}\xi_{j} \overline{g_{k}}]\frac{\overline{u}+1}{\eta}+\overline{u} < 0. \end{aligned} \label{e2.6} \end{equation} which is a contradiction and implies that \eqref{e2.4} holds. This completes the proof. \end{proof} \begin{remark} \label{rmk2.1} \rm It follows that the bounded solution $\widetilde{x} (t)$ can be defined on $[0, \infty)$ according to the theory of functional differential equations in \cite{h1}. \end{remark} \begin{lemma} \label{lem2.2} Suppose that {\rm (H1)--(H3)} hold. Let $x^{*}(t)=(x^{*}_{1}(t), x^{*}_{2}(t),\dots, x^{*}_{n}(t))^{T} $ be the solution of \eqref{e1.1} with initial value $ \varphi^{*}=(\varphi^{*}_{1}(t), \varphi^{*}_{2}(t), \dots, \varphi^{*}_{n}(t))^{T} $, and $ x(t)=(x_{1}(t), x_{2}(t),\dots,x_{n}(t))^{T} $ be the solution of \eqref{e1.1} with initial value $ \varphi=(\varphi _{1}(t), \varphi _{2}(t), \dots, \varphi _{n}(t))^{T}$. Then there exist constants $M_{\varphi}>1$ such that $$ |x_{i}(t)-x^{*}_{i}(t)|\leq M_{\varphi} \|\varphi-\varphi^{*}\|e^{-\lambda t}, \quad \forall t>0, \; i=1, 2, \dots, n. $$ \end{lemma} \begin{proof} Let $y(t)=\{y_{ j}(t) \}=\{x_{ j}(t)-x^{\ast}_{ j}(t) \}=x(t)-x^{*}(t)$. Then \begin{align*} y_{i}^{'}(t) &= -c_{i}(t)[x_{i}(t)-x^{\ast}_{i}(t)] +\sum_{j=1}^{n}a_{ij}(t)\big[f_{j}(x_{j}(t-\widetilde{\tau}_{j}(t))) -f_{j}(x^{\ast}_{j}(t-\widetilde{\tau}_{j}(t)))\big]\\ &\quad +\sum_{j=1}^{n}\sum_{k=1}^{n}b_{ijk}(t)\big[g_{j}(x_{j} (t-\tau_{j}(t)))g_{k}(x_{k}(t-\tau_{k}(t)))\\ &\quad - g_{j}(x^{\ast}_{j}(t-\tau_{j}(t)))g_{k}(x^{\ast}_{k} (t-\tau_{k}(t)))\big] \end{align*} where $ i=1, 2, \dots, n$. Next, define a Lyapunov functional as \begin{equation} V_{i }(t) = |y_{i }(t)|e^{\lambda t}, \quad i=1, 2, \dots, n. \label{e2.7} \end{equation} By \eqref{e2.6} and \eqref{e2.7} it follows that \begin{equation} \begin{aligned} D^+(V_{i }(t)) & \leq D^+(|y_{i}(t)|)e^{\lambda t}+\lambda|y_{i}(t)|e^{\lambda t}\\ & \leq (\lambda-c_{i}(t))|y_{i}(t)|e^{\lambda t}+\{\sum_{j=1}^{n}|a_{ij}|(t)L_{j}|y_{j}(t-\widetilde{\tau}_{j}(t))|\\ &\quad + \sum_{j=1}^{n}\sum_{k=1}^{n}|b_{ijk}(t)|[\overline{g_{k}} M_{j}|y_{j}(t-\tau_{j}(t))| +\overline{g_{j}}M_{k}|y_{k}(t-\tau_{k}(t))|]\}e^{\lambda t} \end{aligned} \label{e2.8} \end{equation} where $i=1, 2, \dots,n$. Let $m^{\ast}>1$ denote a real number such that $$ m^{\ast}\xi_{i}>\|\varphi-\varphi^{*}\| =\sup_{-\tau\leq s\leq0}\max_{1\leq j\leq n } |\varphi_{ j}(s)-\varphi_{j}^{*}(s)|>0, \quad i=1, 2, \dots, n. $$ Then by \eqref{e2.7}, we have $$ V_{i }(t) = |y_{i }(t)|e^{\lambda t}< m^{\ast}\xi_{i} ,\quad \text{for all } t\in [-\tau, 0], \; i=1, 2, \dots, n. $$ Thus we can claim that \begin{equation} V_{i }(t) = |y_{i }(t)|e^{\lambda t}< m^{\ast}\xi_{i} , \quad \text{for all } t>0, \; i=1, 2, \dots, n.\label{e2.9} \end{equation} Otherwise, there must exist $i \in \{ 1, 2, \dots, n \}$ and $t_{i}>0$ such that \begin{equation} V_{i}(t_{i})=m^{\ast}\xi_{i},\quad V_{j}(t)0 $$ This contradicts (H3), then \eqref{e2.9} holds. Letting $M_{\varphi}>1$, such that \begin{equation} \max_{1\leq i\leq n}\{m^{\ast}\xi_i \}\leq M_{\varphi}\|\varphi-\varphi^{*}\|, \quad i=1,2,\dots,n.\label{e2.12} \end{equation} In view of \eqref{e2.9} and \eqref{e2.12}, we obtain $$ |x_{i}(t)-x^{*}_{i}(t)|=|y_{i}(t)|\leq \max_{1\leq i\leq n}\{m\xi_i \}e^{-\lambda t} \leq M_{\varphi} \|\varphi-\varphi^{*}\|e^{-\lambda t}, $$ where $i=1,2,\dots,n$, $t>0$. This completes the proof. \end{proof} \begin{remark} \label{rmk2.2} \rm If $x^{*}(t)=(x^{*}_{1}(t), x^{*}_{2}(t),\dots,x^{*}_{n}(t))^{T} $ is the $T$-anti-periodic solution of \eqref{e1.1}, it follows from Lemma 2.2 and the Definition \ref{def2.1} that $x^{*}(t)$ is globally exponentially stable. \end{remark} \section{Main Results} In this section,we present our main result that there exists the exponentially stable anti-periodic solution of \eqref{e1.1}. \begin{theorem} \label{thm3.1} Assume that {\rm (H1)--(H3)} are satisfied. Then \eqref{e1.1} has exactly one $T$-anti-periodic solution $x^{*}(t)$. Moreover, this solution is globally exponentially stable. \end{theorem} \begin{proof} Let $v(t)= (v_{1}(t), v_{2}(t),\dots, \ v_{n}(t))^{T} $ is a solution of \eqref{e1.1} with initial conditions \begin{equation} v_{i}(s)=\varphi^{v}_{i}(s), \quad |\varphi^{v}_{i}(s)|<\xi_{i}\frac{\overline{u}+1}{\eta} , \quad s\in (-\tau, 0], \; i=1,2,\dots,n.\label{e3.1} \end{equation} Thus according to Lemma 2.1, the solution $v(t)$ is bounded and \begin{equation} |v_{i}(t)|<\xi_{i}\frac{\overline{u}+1}{\eta} , \quad \text{for all } t\in \mathbb{R}, \; i=1,2,\dots,n.\label{e3.2} \end{equation} From \eqref{e2.1}, we obtain \begin{equation} \begin{aligned} &((-1)^{m+1}v_{i} (t + (m+1)T))'\\ &=(-1)^{m+1}\{-c_{i}(t+(m+1)T)v_{i}(t+(m+1)T)\\ &\quad +\sum_{j=1}^{n}a_{ij}(t+(m+1)T)f_{j}(v_{j} (t+(m+1)T-\widetilde{\tau}_{j}(t+(m+1)T)))\\ &\quad +\sum_{j=1}^{n}\sum_{k=1}^{n}b_{ijk}(t+(m+1)T) g_{j}(v_{j}(t+(m+1)T-\tau_{j}(t+(m+1)T)))\\ &\quad\times g_{k}(v_{k}(t+(m+1)T-\tau_{k}(t+(m+1)T))) +u_{i}(t+(m+1)T)\}\\ &= -c_{i}(t)[(-1)^{m+1}v_{i}(t+(m+1)T)]+\sum_{j=1}^{n}a_{ij}(t) \\ &\times f_{j}[(-1)^{m+1}v_{j}((t+(m+1)T)-\widetilde{\tau}_{j}(t+(m+1)T))]\\ &\quad +\sum_{j=1}^{n}\sum_{k=1}^{n}b_{ijk}(t)g_{j}[(-1)^{m+1}v_{j} ((t+(m+1)T)-\tau_{j}(t+(m+1)T))]\\ &\quad \times g_{k}[(-1)^{m+1}v_{k}((t+(m+1)T)-\tau_{k}(t+(m+1)T))] +u_{i}(t) \end{aligned} \label{e3.3} \end{equation} where $i=1, 2, \dots,n$. Thus $(-1)^{m+1} v (t + (m+1)T)$ are the solutions of \eqref{e1.1} on $\mathbb{R}$ for any natural number $m$. Then, from Lemma 2.2, there exists a constant $M>0$ such that \begin{equation} \begin{aligned} &|(-1)^{m+1}v_{i} (t + (m+1)T)-(-1)^{m} v_{i}(t + mT)|\\ &\leq M e^{-\lambda (t + mT)}\sup_{-\tau\leq s\leq0}\max_{1\leq i\leq n}|v_{i} (s + T)+ v_{i} (s)|\\ &\leq 2e^{-\lambda (t + mT)} M \max_{1\leq i\leq n}\{\xi_{i}\frac{\overline{u}+1}{\eta}\}, \quad \forall t + mT>0, \; i=1, 2, \dots, n. \end{aligned}\label{e3.4} \end{equation} Thus, for any natural number $m$, we have \begin{equation} (-1)^{m+1} v_{i} (t + (m+1)T) = v_{i} (t ) +\sum_{k=0}^{m}[(-1)^{k+1} v _{i}(t + (k+1)T)-(-1)^{k} v_{i} (t + kT)]. \label{e3.5} \end{equation} Hence, \begin{equation} |(-1)^{m+1} v_{i} (t + (m+1)T)| \leq | v_{i} (t )| +\sum_{k=0}^{m}| (-1)^{k+1} v _{i}(t + (k+1)T)-(-1)^{k} v_{i} (t + kT)|, \label{e3.6} \end{equation} where $i =1,2,\dots,n$. In view of \eqref{e3.4}, we can choose a sufficiently large constant $N>0$ and a positive constant $\alpha $ such that \begin{equation} |(-1)^{m+1} v_{i} (t + (m+1)T)-(-1)^{m } v_{i} (t + mT)| \leq \alpha (e^{-\lambda T } )^{m}, \label{e3.7} \end{equation} for all $ m >N$, $i=1, 2, \dots, n$, on any compact set of $\mathbb{R}$. Obviously, together with \eqref{e3.5}, \eqref{e3.6} and \eqref{e3.7}, $ \{(-1)^{m} v (t + mT)\}$ uniformly converges to a continuous function $x^{*}(t)=(x^{*}_{1}(t), x^{*}_{2}(t),\dots,x^{*}_{n}(t))^{T}$ on any compact set of $\mathbb{R}$. Now we show that $x^{*}(t)$ is $T$-anti-periodic solution of \eqref{e1.1}. Firstly, $x^{*}(t)$ is $T$-anti-periodic, since \begin{align*} x^{*}(t+T) &=\lim_{m\to \infty}(-1)^{m } v (t +T+ m T)\\ &=-\lim_{(m+1)\to \infty}(-1)^{m+1 } v (t + (m +1)T)=-x^{*}(t ). \end{align*} secondly, we prove that $x^{*}(t)$ is a solution of \eqref{e1.1}. Because of the continuity of the right-hand side of \eqref{e1.1}, \eqref{e3.3} implies that $ \{((-1)^{m+1} v (t +(m+1)T))'\}$ uniformly converges to a continuous function on any compact subset of $\mathbb{R}$. Thus, letting $m \to\infty$, we can easily obtain \begin{equation} \begin{aligned} \frac{d}{dt}\{x^{*}_{i}(t)\} &= -c_{i}(t)x^{*}_{i}(t)+ \sum_{j=1}^{n}a_{ij}(t)f_{j}(x^{*}_{j}(t-\widetilde{\tau}_{j}(t)))\\ &\quad +\sum_{j=1}^{n}\sum_{k=1}^{n}b_{ijk}(t)g_{j}(x^{*}_{j} (t-\tau_{j}(t))) g_{k}(x^{*}_{k}(t-\tau_{k}(t)))+u_{i}(t), \end{aligned} \label{e3.8} \end{equation} where $i=1, 2, \dots, n$. Therefore, $x^{*}(t)$ is a solution of \eqref{e1.1}. Finally, by applying Lemma 2.2, it is easy to check that $x^{*}(t)$ is globally exponentially stable. This completes the proof. \end{proof} \section{An Example} In this section, a simple example is provided to illustrate our results. Consider the high-order cellular neural network with delays \begin{equation} \label{e4.1} \begin{aligned} x_{1}'(t) &= -x_{1}(t)+\frac{1}{4}|\sin t|f_{1}(x_{1}(t-1)) +\frac{1}{36}|\cos t|f_{2}(x_{2}(t-2))\\ &\quad + \frac{1}{72}\sin t g^{2}_{1}(x_{1}(t-1)) +\frac{1}{36}\cos t g_{1}(x_{1}(t-1))g_{2}(x_{2}(t-2))\\ &\quad+\frac{1}{72}\cos t g^{2}_{2}(x_{2}(t-2))+\frac{1}{9}\sin t ,\\ x_{2}'(t) &= -x_{2}(t)+\frac{1}{36}|\cos t|f_{1}(x_{1}(t-1)) +\frac{1}{4}|\sin t|f_{2}(x_{2}(t-2))\\ &\quad + \frac{1}{72}\cos t g^{2}_{1}(x_{1}(t-1)) +\frac{1}{36}\cos t g_{1}(x_{1}(t-1))g_{2}(x_{2}(t-2))\\ &\quad +\frac{1}{72}\sin t g^{2}_{2}(x_{2}(t-2))+\frac{1}{9}\sin t\,, \end{aligned} \end{equation} where $f_{1}(x)=f_{2}(x)= x$, $g_{1}(x)=g_{2}(x)= \arctan x$, $c_{1}(t)=c_{2}(t)=1, u_{1}(t)=\frac{1}{9}\sin t$, $u_{2}(t)=\frac{1}{9}\sin t$, $a_{11}(t)=a_{22}(t)=\frac{1}{4}|\sin t|$, $a_{12}(t)=a_{21}(t)=\frac{1}{36}|\cos t|$, $b_{111}(t)=b_{222}(t)=\frac{1}{72}\sin t$, $b_{112}(t)=b_{121}(t)=b_{122}(t)=b_{211}(t)=b_{212}(t)=b_{221}(t)= \frac{1}{72}\cos t$. Noting that $$ L_{1}=L_{2}=M_{1}=M_{2}=1,\quad \overline{g_{1}}=\overline{g_{2}}=\frac{\pi}{2}. $$ Therefore, there exist constants $\eta=\frac{1}{2}$, $ \lambda=\frac{1}{1800}$ and $\xi_{1}=\xi_{2}=1$, such that for all $t>0$, $i=1,2$, there holds $$ [\lambda-c_{i}(t)]\xi_{i}+[\sum_{j=1}^{2}a_{ij}(t)L_{j}\xi_{j} +\sum_{j=1}^{2}\sum_{k=1}^{2} b_{ijk}(t)(\overline{g_{k}}M_{j}\xi_{j} +\overline{g_{j}}M_{k}\xi_{k})]e^{\lambda \tau}<-\eta, $$ which implies that system \eqref{e4.1} satisfy all the conditions in Theorem 3.1. Hence, \eqref{e4.1} has exactly one $\pi$-anti-periodic solution. Moreover, this solution is globally exponentially stable. This fact is verified in the numerical simulation in Figure 1. \begin{figure}[ht] \label{fig1} \begin{center} \includegraphics[width=0.48\textwidth]{fig1} \includegraphics[width=0.48\textwidth]{fig2} \end{center} \caption{Numerical solution $(x_{1 }(t),x_{2}(t))$ of system \eqref{e4.1} for $(\varphi_{1}(s),\varphi_{2}(s) )=(0.5,0.8)$.} \end{figure} We remark that \eqref{e4.1} is a very simple form of high-order cellular neural networks with delays. However, the results in the references can not be applicable for obtaining existence and exponential stability of the anti-periodic solutions. This makes our results new. \subsection*{Acknowledgements} The authors would like to express the sincere appreciation to the anonymous referee for his/her helpful comments in improving the presentation and quality of this paper. \begin{thebibliography}{00} \bibitem{a1} A. R. Aftabizadeh, S. Aizicovici, N. H. Pavel; \emph{On a class of second-order anti-periodic boundary value problems}, J. Math. 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