Global exponential stability of generalized recurrent neural networks with discrete and distributed delays
TLDR
A linear matrix inequality (LMI) approach is developed to establish sufficient conditions for the RNNs to be globally exponentially stable, and the existence and uniqueness of the equilibrium point under mild conditions is proved.About:
This article is published in Neural Networks.The article was published on 2006-06-01 and is currently open access. It has received 671 citations till now. The article focuses on the topics: Exponential stability & Recurrent neural network.read more
Citations
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Journal ArticleDOI
Stochastic Synchronization of Markovian Jump Neural Networks With Time-Varying Delay Using Sampled Data
TL;DR: Two delay-dependent criteria are derived to ensure the stochastic stability of the error systems, and thus, the master systems stochastically synchronize with the slave systems.
Journal ArticleDOI
A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks
TL;DR: The purpose of this paper is to provide a comprehensive review of the research on stability of continuous-time recurrent Neural networks, including Hopfield neural networks, Cohen-Grossberg neural networks and related models.
Journal ArticleDOI
Global Synchronization for Discrete-Time Stochastic Complex Networks With Randomly Occurred Nonlinearities and Mixed Time Delays
Zidong Wang,Yao Wang,Yurong Liu +2 more
TL;DR: By constructing a novel Lyapunov-like matrix functional, the idea of delay fractioning is applied to deal with the addressed synchronization analysis problem and several delay-dependent sufficient conditions are obtained which ensure the asymptotic synchronization in the mean square sense for the discrete-time stochastic complex networks with time delays.
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Synchronization and State Estimation for Discrete-Time Complex Networks With Distributed Delays
TL;DR: A synchronization problem is investigated for an array of coupled complex discrete-time networks with the simultaneous presence of both the discrete and distributed time delays and an LMI approach is developed for the state estimation problem.
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Stability analysis for stochastic Cohen-Grossberg neural networks with mixed time delays
TL;DR: It is shown that the addressed stochastic Cohen-Grossberg neural networks with mixed delays are globally asymptotically stable in the mean square if two LMIs are feasible, where the feasibility of LMIs can be readily checked by the Matlab LMI toolbox.
References
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Book
Linear Matrix Inequalities in System and Control Theory
TL;DR: In this paper, the authors present a brief history of LMIs in control theory and discuss some of the standard problems involved in LMIs, such as linear matrix inequalities, linear differential inequalities, and matrix problems with analytic solutions.
Book
Theory of Functional Differential Equations
TL;DR: In this paper, Liapunov functional for autonomous systems is used to define the saddle point property near equilibrium and periodic orbits for linear systems, which is a generalization of the notion of stable D operators.
Proceedings ArticleDOI
An integral inequality in the stability problem of time-delay systems
TL;DR: In this paper, an integral inequality is derived, and applied to the stability problem of time-delay systems using discretized Lyapunov functional formulation, and a simpler stability criterion is derived.
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