The stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays and reaction-diffusion terms.

abstract

• The global asymptotic stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays and reaction-diffusion terms is investigated. Under some suitable assumptions and using Lyapunov-Krasovskii functional method, we apply the linear matrix inequality technique to propose some new sufficient conditions for the global asymptotic stability of the addressed model in the stochastic sense. The mixed time delays comprise both the time-varying and continuously distributed delays. The effectiveness of the theoretical result is illustrated by a numerical example.

authors

• Huang, Tingwen

published proceedings

• Cogn Neurodyn

author list (cited authors)

• Tan, J., Li, C., & Huang, T.

citation count

• 8

complete list of authors

• Tan, Jie||Li, Chuandong||Huang, Tingwen

publication date

• April 2015

publisher

• Springer Nature  Publisher

published in

• Cognitive Neurodynamics  Journal

keywords

• Global Asymptotic Stability
• Mixed Delays
• Poincare Inequality
• Reaction–diffusion
• Stochastic Cohen–grossberg Neural Network

PubMed Central ID

• 25834649

Digital Object Identifier (DOI)

• 10.1007/s11571-014-9316-y

start page

• 213

end page

• 220

volume

• 9

issue

• 2

URL

• http://dx.doi.org/10.1007/s11571-014-9316-y