Bifurcation Analysis for Simplified Five-Neuron Bidirectional Associative Memory Neural Networks with Four Delays

The paper deals with the stability and bifurcation analysis of a class of simplified five-neuron bidirectional associative memory neural networks with four     

Stability Analysis for a Class of Impulsive Bidirectional Associative Memory (BAM) Neural Networks with Distributed Delays and Leakage Time-Varying Delays

Neural Processing Letters - In this paper, by employing contraction mapping principle theorem and by finding suitable Lyapunov–Krasovskii functional, some sufficient conditions are given for...     

Global Exponential Stability of High-Order Bidirectional Associative Memory (BAM) Neural Networks with Proportional Delays

Neural Processing Letters - This paper considers the global exponential stability (GES) of high-order bidirectional associative memory (BAM) neural networks with proportional delays. Here,...     

Almost Periodic Solution for Shunting Inhibitory Cellular Neural Networks with Time-varying Delays and Variable Coefficients

In this paper, a class of two-dimensional shunting inhibitory cellular neural networks with time-varying delays and variable coefficients as following system

Pseudo Almost Periodic Solutions for High-Order Hopfield Neural Networks with Time-Varying Leakage Delays

In this paper, high-order Hopfield neural networks with time-varying leakage delays are investigated. By applying Lyapunov functional method and differential inequality techniques, a set of sufficient conditions are obtained for the existence and exponential stability of pseudo almost periodic solutions of the model. Some simulations are carried out to support the theoretical findings. Our results improve and generalize those of the previous studies.     

时滞杂交双向联想记忆神经网络的全局指数稳定性

在近十几年里,已提出了一类与双向联想记忆相联系的神经网络模型,这些模型推广了单层自联想Hebbian相关器为两层异联想模式匹配器,因而,这类网络在模式识别、信号与图像处理等领域中有广阔的应用前景．研究了带离散时滞杂交双向联想记忆神经网络的收敛特性,利用Halanay型不等式获得了网络全局指数稳定性的充分条件,所得结果是与时滞无关的;已证明利用Halanay型不等式获得的结果改进了由Lyapunov方法获得的结果,而且获得的结果容易判定,并且给出了一个数值例子以说明所得结论的正确性．     

联想记忆与人工神经网络

联想记忆是人类记忆的基本方式,本文通过对人类联想记忆的本质及其规律的分析,讨论了如何用人工神经网络的模型来实现这种记忆形式,同时也指出了这种模拟的不足之处及需要解决的问题。     

变时滞神经网络的全局指数稳定性

利用M矩阵理论,同构理论以及不等式技巧,研究了一类变时滞神经网络平衡点的存在性和惟一性问题。同时利用M矩阵理论,反证法以及不等式技巧,得到了变时滞神经网络系统惟一的平衡点的全局指数稳定性的充分条件。通过判断由神经网络的权系数、自反馈函数以及激励函数构造的矩阵是否为M矩阵,即可以检验该变时滞神经网络系统的全局指数稳定性。该判据易于用Matlab进行检验,最后给出一个仿真示例进一步证明了判据的有效性。     

含离散和分布时变时延神经网络系统的指数稳定性

针对一类含有离散和分布时延神经网络,在神经激活函数较弱的约束条件下,通过定义一个更具一般性的Lyapunov泛函,使用凸组合技术,得到了新的基于线性矩阵不等式表示的指数稳定性判据.与现有结果相比,这些判据具有较小的保守性.仿真算例表明,得到的结果是有效的且保守性小.     

时变时滞神经网络系统的时滞依赖的鲁棒稳定性准则

基于Lyapunov稳定性理论和线性矩阵不等式技术,针对一类带有范数有界不确定性的时变时滞神经网络系统,给出时滞依赖的鲁棒稳定性准则.系统稳定的充分条件是在激励函数满足一类更为通用的条件下得到的,即激励函数不必是单调可微的,并且消除对时变时滞导数的限制.所给的准则可用Matlab中的线性矩阵不等式控制工具箱进行验证.仿真结果进一步证明结论的有效性.     

Global Lagrange Stability for Takagi-Sugeno Fuzzy Cohen-Grossberg BAM Neural Networks with Time-varying Delays

This paper concerns the globally exponential stability in Lagrange sense for Takagi-Sugeno (T-S) fuzzy Cohen-Grossberg BAM neural networks with time-varying delays. Based on the Lyapunov functional method and inequality techniques, two different types of activation functions which include both Lipschitz function and general activation functions are analyzed. Several sufficient conditions in linear matrix inequality form are derived to guarantee the Lagrange exponential stability of Cohen-Grossberg BAM neural networks with time-varying delays which are represented by T-S fuzzy models. Finally, simulation results demonstrate the effectiveness of the theoretical results.     

A New Stability Condition for Uncertain Fuzzy Hopfield Neural Networks with Time-varying Delays

International Journal of Control, Automation and Systems - In this paper, the global asymptotic stability of uncertain fuzzy Hopfield neural networks(UFHNNs) with time-varying delays is...     

高阶时滞Hopfield网络的吸引域和指数收敛速度

利用一些实分析技巧和Liapunov方法,估计了具有时滞的高阶Hopfield联想记忆神经网络的吸引域和其中每一点趋向平衡点的指数收敛速度,这些结果可用于此类网络的设计及容错性评价。     

混沌神经网络及其在联想记忆中的应用

提出了一种新型的混沌神经网络模型及其相应的学习算法。该学习算法利用了输入模式各元素之间的关联性信息。此文的神经网络可以用于多值模式的联想记忆,与现有的混沌神经网络相比,具有更好的性能。     

Stability and Existence of Periodic Solutions of Periodic Cellular Neural Networks with Time-Vary Delays

By using the continuation theorem of Mawhins coincidence degree theory and constructing a suitable Lyapunov function, some new sufficient conditions are obtained ensuring existence and global asymptotical stability of periodic solution of cellular neural networks with periodic coefficients and delays, which do not require the activation functions to be differentiable and monotone nondecreasing. A numerical example is given to illustrate that the criteria are feasible. These results are helpful to design globally asymptotically stable and periodic oscillatory cellular neural networks.     

具有内连接的指数多值双向联想记忆模型

C_CWang的多值指数双向联想记忆模型 (MVeBAM)是一种高存储容量的联想神经网络. 本文在MVe BAM的基础上通过引入自相关项 (或内连接 )提出了一个新的具有内连接的多值指数双向联想记忆模型, 推广了MVeBAM. 通过定义简单的能量函数证明了其在同、异步方式下的稳定性, 从而保证了所学模式对成为被推广的MVeBAM(EMVeBAM)的稳定点. 最后, 计算机模拟证实了EMVeBAM比MVeBAM具有更高的存储容量和更好的纠错性能.     

Global Asymptotic Stability of Periodic Solutions for Neutral-Type BAM Neural Networks with Delays

Neural Processing Letters - In this paper, we study the neutral-type BAM neural networks with time-varying delays. By applying the continuation theorem and some analysis techniques, some sufficient...     

离散Hopfield联想记忆神经网络的渐近行为

该文对一类离散Hopfield联想记忆神经网络的渐近行为进行了讨论,首先提出这类I／O函数取为Sigmoid型函数的离散Hopfield联想记忆神经网络的数学模型,讨论并给出了这种模型的一系列性质,例如运动轨迹的有界性,平衡点的唯一性以及渐近稳定性等,得到了平衡点渐近稳定的充分条件,检验这种神经网络模型的渐近稳定性,只需要测试一个特定矩阵的定性性质或特定不等式即可,这些结果可用于离散Hopfield联想记忆神经网络的综合过程。     

Finite Time State Estimation of Complex-valued BAM Neutral-type Neural Networks with Time-varying Delays

International Journal of Control, Automation and Systems - This paper considers the finite time state estimation problem of complex-valued bidirectional associative memory (BAM) neutral-type neural...