具有扩散率Ayala模型的概周期解

本文研究了非自治Ayala模型的概周期和周期系统,我们得到在一定条件下,其概周期系统存在唯一全局吸引的概周期解且其概周期解在壳扰动下是稳定的。在与概周期情形类似的条件下我们得到其w-周期系统存在唯一全局吸引的w-周期解。     

Hopfield神经网络概周期解的存在性和全局吸引性

该文研究Ｈｏｐｆｉｅｌｄ神经网络概周期解的存在性和全局吸性,获得了该网络存在唯一概周期解的充分条件和所有解收敛于此概周期解的充分条件。     

强平均解与概周期解的存在性

本文定义了概周期微分方程的强平均解,利用强平均解的性质,讨论了强平均解与概周期解的关系,从而建立了概周期解存在的若干定理。     

二次概周期系数微分方程的概周期解

利用指数二分性,Schauder不动点定理和Grownwall不等式证明了一类概周期系数微分方程的概周期解、有界解的存在唯一性及概周期解的全局吸引性.     

一个概周期锁相环路方程的概周期解的存在唯一性和渐近稳定性

本文研究了一个概周期锁相环路方程的概周期解的存在唯一性及渐近稳定性,得到了保证系统存在唯一渐近稳定的概周期解的充分条件     

全局渐近稳定性质与概周期解的存在唯一性

众所周知,周期系统解的有界性蕴含着周期解的存在性。然而对于概周期系统(1)来说,即使在n=1的情况下其解的有界性也未必蕴含着概周期解的存在性。因此,在讨论(1)的概周期解的存在性时,必需同时考虑有界解的某种稳定性质。 本文首先证明当研究概周期系统(1)的概周期解φ(t)的稳定性时,可假设φ(t)是明显解。其次,我们利用李雅普诺夫函数和比较原理得到了(1)的零解为全局等度(均匀)渐近稳定的一些结果。最后,我们亦得到了(1)存在唯一概周期解的充分条件。所得结果推广了[1,11,13]中有关结论。     

带梯度算子二阶方程的渐近概周期解

利用渐近概周期函数的性质得到带梯度算子二阶方程的渐近概周期解在C（R^-）中的存在性．同时利用迭代法和线性常微分方程的概周期解的存在性和唯一性,得到R上此方程渐近概周期解的存在和唯一性．     

无穷维随机微分方程的渐近概周期解

该文引入了渐近θ-概周期随机过程的概念,并在算子半群理论框架下研究了一类带有渐近概周期系数的无穷维随机微分方程,利用随机分析理论建立了此类随机微分方程渐近θ-概周期解的存在性.此外该文还引入了依路径分布渐近概周期过程的概念,并证明了上述渐近θ-概周期解还是依路径分布渐近概周期的.值得注意的是,在早期的研究结果中,建立的均是更弱的一维分布渐近概周期解的存在性.     

具有反馈控制的离散两种群竞争系统的概周期解

对于具有反馈控制的离散概周期两种群竞争系统的概周期解问题,进行了深入的讨论,得到了该系统存在唯一的一致渐近稳定概周期解的充分条件.     

一致渐近稳定和周期解、概周期解的存在性

本文建立了系统解一致稳定、解一致渐近稳定和某种Liapunov函数存在的充要条件,并且得到:满足Lipschitz条件而且解一致渐近稳定的概周期系统有唯一的概周期解,周期系统有唯一的周期解。     

EXISTENCE AND ATTRACTIVITY OF ALMOST PERIODIC SOLUTION FOR HOPFIELD NEURAL NETWORKS WITH VARIABLE COEFFICIENTS

This paper is to study the existence and attractivity of almost periodic solution for Hopfield-Type delay cellular neural networks(HDCNNs) with variable coefficientsby combining the theory of the exponential dichotomy and Lyapunov functionals method and combine with some analysis techniques. We obtain some sufficient conditions to ensure the networks to have a unique almost periodic solution, and all other solutions converge to this solution.     

Almost periodic solutions of recurrent neural networks with continuously distributed delays

In this paper, a class of recurrent neural networks with continuously distributed delays is discussed. Without resorting to the theory of exponential dichotomy, several new sufficient conditions are obtained ensuring the existence of an almost periodic solution for this model based on a special functional and analysis technique. Moreover, by constructing suitable Lyapunov functions, the attractivity and exponential stability of the almost periodic solution are also considered for the system. The results obtained are helpful to design globally stable almost periodic oscillatory neural networks. A numerical example is given to show the feasibility of the results obtained.     

Existence and exponential stability of almost periodic solution for shunting inhibitory cellular neural networks with impulses

In this paper, by using the contraction principle and Gronwall–Bellman’s inequality, some sufficient conditions are obtained for checking the existence and exponential stability of almost periodic solution for shunting inhibitory cellular neural networks (SICNNs) with impulse. Our results are essentially new. It is the first time that the existence of almost periodic solutions for the impulsive neural networks are obtained.     

Existence and global exponential stability of almost periodic solution for quaternion-valued high-order Hopfield neural networks with delays via a direct method

This paper deals with the existence and global exponential stability of almost periodic solutions for quaternion-valued high-order Hopfield neural networks with delays by a direct approach. Based on the contraction mapping principle, sufficient conditions are derived to ensure the existence and uniqueness of almost periodic solutions for the networks under consideration. By constructing a suitable Lyapunov function, the global exponential stability criterion of the almost periodic solution are derived. Finally, two numerical examples are given to illustrate the main results of this paper.     

Existence and exponential stability of positive almost periodic solutions for high-order Hopfield neural networks

This paper is concerned with the existence and exponential stability of positive almost periodic solutions of high-order Hopfield neural networks (HHNNs) with time-varying delays. Some sufficient conditions for the existence and exponential stability of positive almost periodic solutions are established.     

Almost periodic solution of Cohen–Grossberg neural networks with bounded and unbounded delays

In this paper, a class of Cohen–Grossberg neural networks with bounded and unbounded delays is discussed. Several new sufficient conditions are obtained ensuring the existence and exponential stability of the almost periodic solution for this model based on inequality analysis technique and combing the exponential dichotomy with fixed point theorem. The obtained results are helpful to design globally exponentially stable almost periodic oscillatory neural networks. Two numerical examples and simulations are also given to show the feasibility of our results.     

Existence and stability of almost periodic solution for Cohen–Grossberg neural networks with variable coefficients

This paper is devoted to the existence and globally exponential stability of almost periodic solution for a class of Cohen–Grossberg neural networks with variable coefficients. By using Banach fixed point theorem and applying inequality technique, we give some sufficient conditions ensuring the existence and globally exponential stability of almost periodic solution. These results have important leading significance in designs and applications of Cohen–Grossberg neural networks. Finally, two examples with their numerical simulations are provided to show the correctness of our analysis.     

具有混合时滞的中立型Hopfield神经网络的概周期解

研究一类具有混合时滞的中立型Hopfield神经网络概周期解.通过运用指数二分性及不动点定理,获得了其概周期解的存在性与全局指数稳定性的充分条件,所得结果是新的,并且推广和改进了已有文献的相关结果.     

Existence and Exponential Stability of Almost Periodic Solution for Hopfield Neural Network Equations with Almost Periodic Imput

By constructing Liapunov functions and building a new inequality, we obtain two kinds of sufficient conditions for the existence and global exponential stability of almost periodic solution for a Hopfield-type neural networks subject to almost periodic external stimuli. In this paper, we assume that the network parameters vary almost periodically with time and we incorporate variable delays in the processing part of the network architectures.