Research Article | Open Access

Lin Lu, Chaoling Li, "Almost Periodic Dynamics for Memristor-Based Shunting Inhibitory Cellular Neural Networks with Leakage Delays", *Computational Intelligence and Neuroscience*, vol. 2016, Article ID 3587271, 13 pages, 2016. https://doi.org/10.1155/2016/3587271

# Almost Periodic Dynamics for Memristor-Based Shunting Inhibitory Cellular Neural Networks with Leakage Delays

**Academic Editor:**Paolo Del Giudice

#### Abstract

We investigate a class of memristor-based shunting inhibitory cellular neural networks with leakage delays. By applying a new Lyapunov function method, we prove that the neural network which has a unique almost periodic solution is globally exponentially stable. Moreover, the theoretical findings of this paper on the almost periodic solution are applied to prove the existence and stability of periodic solution for memristor-based shunting inhibitory cellular neural networks with leakage delays and periodic coefficients. An example is given to illustrate the effectiveness of the theoretical results. The results obtained in this paper are completely new and complement the previously known studies of Wu (2011) and Chen and Cao (2002).

#### 1. Introduction

It is common knowledge that shunting inhibitory cellular neural networks (SICNNs) have a wide application in many fields such as image processing, signal processing, pattern recognition, psychophysics, speech, perception, robotics, and vision [1–3]. Thus, the theoretical analysis and applied research on SICNNs have attracted worldwide attention. During the past decades, memristor which is a new circuit element has received much attention due to its wide range of applications in computer, physics, electronic engineering, and so on [4, 5]. In particular, memristor has memory function and nanometer dimensions. The former can help us to deal with nanocomputing and the latter can provide a very high density and is less power hungry. The memristor can exhibit features as what the neurons in the human brain possess [4].

In practical implementation, the time delays often occur in neural networks due to the finite switching speed of the neuron amplifiers and the finite signal transmission velocity. Here, we would like to point out that a typical time delay called leakage (or forgetting) delay may occur in the negative feedback term of the neural networks and plays an important role in characterizing the dynamical behavior of neural networks [6–11]. For example, time delay in the stabilizing negative feedback term may destabilize a system [12]. Balasubramaniam et al. [13] argued that the existence and uniqueness of the equilibrium point have nothing to do with time delays and initial conditions. Thus, it is important to study the leakage delays’ effect on the dynamical behavior of memristor-based neural networks. In recent years, there is some work on this topic. We refer the readers to [14–16].

As is known to us, periodic oscillation of neural networks plays an important role in the daily life of human beings. Periodic oscillation of neural networks has been widely applied in many biological and cognitive activities. For example, periodic oscillatory or chaotic phenomena often occur in the human brain. Thus, some authors investigate the periodic oscillatory dynamical behavior of neural networks for grasping the mechanism of the human brain. We refer the readers to [17–19]. However, in many cases, the periodic parameters of neural networks may experience certain perturbations and then they may be not periodic. Thus, it is more reasonable to characterize the reality of neural networks with almost periodic parameters. In recent years, many authors consider the almost periodic oscillation of neural networks with or without delay and numerous good results have been available. For example, Liu et al. [20] focused on the almost periodic solution of impulsive Hopfield neural networks with finite distributed delays by applying fixed point theorems, Lyapunov functional, and some inequality techniques. Li et al. [21] investigated the existence and global exponential stability of almost periodic solution for high-order BAM neural networks with delays on time scales. By using a fixed point theorem and by constructing a suitable Lyapunov functional, authors established some sufficient conditions to ensure the existence and global exponential stability of almost periodic solution for high-order bidirectional associative memory neural networks with delays on time scales. Huang [22] presented some sufficient conditions for the existence and exponential stability of almost periodic solutions for fuzzy cellular neural networks with time-varying delays. Li et al. [23] established some sufficient conditions to ensure the existence and stability of pseudo almost periodic solution for neutral type high-order Hopfield neural networks with delays in leakage terms on time scales by means of fixed point theorem and the theory of calculus on time scales. For more results on this aspect, we refer the readers to [24–34]. To the best of our knowledge, there are no results on the existence and stability of almost periodic solution of memristor-based shunting inhibitory cellular neural networks with leakage delays.

Inspired by the discussions above, in this article, we considered the following memristor-based shunting inhibitory cellular neural networks with leakage delays:where , , represents the cell at the position of the lattice, the -neighborhood of is is the activity of the cell is the external input to , the constant represents the passive decay rate of the cell activity, the activation function is a positive continuous function representing the output or firing rate of the cell , and denote the leakage delay and transmission delay at time , is memristive synaptic weights (which means the connection or coupling strength of postsynaptic activity of the cell transmitted to the cell ), which is defined as follows:for , or when , when are threshold level functions, are threshold level, and and are all continuous functions. The initial states associated with (3) are given by where

The main purpose of this article is to investigate the existence and exponential stability of the almost periodic solutions for system (1). With the aid of new Lyapunov function techniques, we establish some new sufficient criteria which guarantee the existence, uniqueness, and exponential stability of the almost periodic solution of system (1). Also, the derived results on the almost periodic solution are applied to prove the existence and stability of periodic solution for memristor-based shunting inhibitory cellular neural networks with leakage delays and periodic coefficients. The obtained results of this article are new and complement previously known publications.

The remainder of the paper is organized as follows. In Section 2, some necessary definitions and lemmas are stated. In Section 3, a set of sufficient criteria which guarantee the global existence and boundedness of any solutions and the existence and exponential stability of an almost periodic solution of neural networks (1) are established. The global exponential periodicity and stability of system (1) are analyzed in Section 4. An example is given to show the correctness of the theoretical predictions in Section 5. A brief conclusion is drawn in Section 6.

#### 2. Preliminaries

In this section, we list several definitions and notations. Suppose ; then is called a set-valued map from to , if, for each point , there exists a nonempty set A set-valued map with nonempty values is said to be upper semicontinuous at , if, for any open set containing , there exists a neighborhood of such that The map is said to have a closed (convex, compact) image if, for each is closed (convex, compact). For , let Given the function , denotes the gradient of and denotes Clarke’s generalized gradient of

In (1), since is discontinuous, the classical definition of the solution for differential equations cannot apply here. To handle this problem, Filippov developed a solution concept for the differential equation with a discontinuous right-hand side. Based on this definition, a differential equation with a discontinuous right-hand side has the same solution set as a certain differential inclusion. In what follows, we use this definition to discuss dynamical behavior of (1). Let the set-valued maps be as follows:for , where denotes the convex closure of a set. Obviously, is all closed, convex, and compact in for each We define the Filippov solution of (1) as the following.

*Definition 1. *A function is said to be a solution of (1) on with initial condition (4), if is absolutely continuous on any compact interval of and satisfies differential inclusions or, equivalently, there exist satisfyingfor a.e. ,

*Definition 2. *A continuous function is said to be almost periodic on if, for any , it is possible to find a real number For any interval with length , there exists a number in this interval, such that for all

*Definition 3. *A continuous function is said to be asymptotically almost periodic on if, for any , there exist , , and in any interval with the length of , such that for all

*Definition 4. *The neural networks model is said to be globally exponentially almost periodic if the state of the neural networks model is globally exponentially convergent to an almost periodic state ; that is, there are constants and such that, for any , In addition, if is a periodic solution (equilibrium), then the neural networks model is said to be globally exponentially periodic (stable).

*Definition 5 (see [35]). * is said to be regular, if, for each and , (i)there exists the usual right or left directional derivative (ii)the generalized directional derivative of at in the direction is defined as then

*Definition 6. *For a locally Lipschitz function , one can define Clarke’s generalized gradient of at point , as follows: where is the set of points where is not differentiable and is an arbitrary set with measure zero.

Lemma 7 (see [36]). *If is Clarke’s regular and is absolutely continuous on any compact interval of , then and are differential for a.a. , and one will have , where is Clarke’s generalized gradient.*

Lemma 8 (see [37]). *Let matrix have nonpositive off-diagonal elements. Then, is a nonsingular -matrix if and only if one of the following conditions holds:*(1)*There exist positive constants such that*(2)*There exist positive constants such that *

Denote , where is a bounded continuous function.

Throughout this paper, we assume that the following conditions are satisfied: (H1)For , , and are continuous functions and are almost periodic; that is, for any , it is possible to find a real number ; for any interval with length , there exists a number in this interval, such that , , , , , and for all (H2)For , is bounded above and below by positive constants and is a bounded continuous function and (H3)There exists constant such that for (H4)There exist positive constants and such that for all and , , where and (H5)There exists a nonempty subset satisfying the following property: if , then there exists such that or (H6)For , for any

#### 3. Boundedness and Almost Periodicity

In this section, we will prove the existence of bounded solution and the exponential stability of almost periodic solution for (1).

Theorem 9. *Assume that assumptions (H1)–(H4) hold. Let be the solution of (1) with initial conditionwhere , and Then,where is in the interval of existence and *

*Proof. *Let be a solution of (1) with initial condition (14). For , there exists satisfyingfor a.a. By (5) and (H3), we haveFor in the interval of existence and , denoteSuppose (16) holds; then, for a given in the interval of existence and , we get for any . Then, for any It follows from (22) thatTherefore, (17) holds. Thus, it suffices to prove (16). Assume that (16) does not hold. Then, there exist , , and such that and (16) holds for all and , and hence . From system (1), we have It follows from (H3) thatwhich is a contradiction and shows that (16) holds. The proof of Theorem 9 is complete.

Lemma 10. *Assume that (H3), (H5), and (H6) hold; then, for any , , one haswhere , *

*Proof. *For any given , , and , we consider three cases.

If , then If , then If or , then it follows from (H4) that there exists such that or Let . In this case, from (H5), we get Based on all the cases above, we can conclude that (26) holds. The proof of Lemma 10 is complete.

Now, we state our main result.

Theorem 11. *If (H1)–(H6) hold, then there exists a unique almost periodic solution for system (1) which is globally exponentially stable; that is, for any other solution of system (1), there exist constants such that for all .*

*Proof. *First, we prove that any solution of (1) is asymptotically almost periodic; that is, for any , there exist , , and in any interval with the length of , such that for all

For any , let and , , , and then we getwhere and are defined as follows:for all andIn view of (H1) and the boundedness of , we can conclude that, for any , there exist , and in any interval with the length of , such that, for any , for all , where is a constant. Letwhere and

In view of (H3), we can choose and such that Let For and , denoteThen, for and , , we haveNow, we define a candidate Lyapunov function as follows: Obviously, is nondecreasing. It follows that for all , where By (H3), we havefor all , where For any given , there exist , such thatCalculating the derivative along the positive half trajectory of (1) yields