Stochastic stability analysis of uncertain genetic regulatory networks with mixed time-varying delays

  • Authors:
  • Wenqin Wang;Shouming Zhong

  • Affiliations:
  • School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China;School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China and Key Laboratory for NeuroInformation of Ministry of Education, Unive ...

  • Venue:
  • Neurocomputing
  • Year:
  • 2012

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Abstract

Genetic regulatory networks have become an important new area of research in the biological and biomedical sciences. This paper presents a robust analysis approach to stochastic asymptotic stability of the uncertain genetic regulatory networks with both mixed time-varying delays and stochastic noise. By choosing an appropriate new Lyapunov functional and employing stochastic analysis methods, some less conservative delay-range-dependent and delay-derivative-dependent stability criteria have been derived in terms of linear matrix inequalities. The important feature is that the obtained stability criteria are applicable to both fast and slow time-varying delays due to the ranges for the time-varying delays have been carefully considered. Finally, three numerical examples are presented to illustrate the effectiveness of the theoretical results.