Optimal regulation of stochastic cellular neural networks using differential minimax game

Ziqian Liu, Raul E. Torres, Nirwan Ansari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present an approach to optimally regulate stochastic cellular neural networks by using differential minimax game. In order to realize the design, we consider the vector of external inputs as a player and that of internal noises as an opposing player. The purpose of this study is to achieve the best rational stabilization in probability for stochastic cellular neural networks, and to attenuate noises to a predefined level with stability margins under an optimal control strategy. A numerical example is given to demonstrate the effectiveness of the proposed approach.

Original languageEnglish (US)
Title of host publication2010 IEEE International 53rd Midwest Symposium on Circuits and Systems, MWSCAS 2010
Pages1214-1217
Number of pages4
DOIs
StatePublished - Sep 20 2010
Event53rd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2010 - Seattle, WA, United States
Duration: Aug 1 2010Aug 4 2010

Publication series

NameMidwest Symposium on Circuits and Systems
ISSN (Print)1548-3746

Other

Other53rd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2010
CountryUnited States
CitySeattle, WA
Period8/1/108/4/10

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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