Global dissipativity of continuous-time recurrent neural networks with time delay

Xiaoxin Liao, Jun Wang

Research output: Contribution to journalArticlepeer-review

124 Citations (Scopus)

Abstract

This paper addresses the global dissipativity of a general class of continuous-time recurrent neural networks. First, the concepts of global dissipation and global exponential dissipation are defined and elaborated. Next, the sets of global dissipativity and global exponentially dissipativity are characterized using the parameters of recurrent neural network models. In particular, it is shown that the Hopfield network and cellular neural networks with or without time delays are dissipative systems.

Original languageEnglish
Pages (from-to)7
Number of pages1
JournalPhysical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics
Volume68
Issue number1
DOIs
Publication statusPublished - 2003
Externally publishedYes

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