reviewIEEE Transactions on Neural Networks and Learning SystemsMay 13, 2014BRONZE OA

A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks

HZHuaguang ZhangZWZhanshan WangDLDerong Liu

State Key Laboratory of Synthetical Automation for Process Industries · Northeastern University · +2 more institutions

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Abstract

Stability problems of continuous-time recurrent neural networks have been extensively studied, and many papers have been published in the literature. 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. Since time delay is inevitable in practice, stability results of recurrent neural networks with different classes of time delays are reviewed in detail. For the case of delay-dependent stability, the results on how to deal with the constant/variable delay in recurrent neural networks are summarized. The relationship among stability results…

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646
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3

Topics & keywords

Topics
Keywords
  • Artificial neural network
  • Recurrent neural network
  • Stability (learning theory)
  • Computer science
  • Types of artificial neural networks
  • Stability conditions
  • Stochastic neural network
  • Diagonal
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