In this paper, we consider the stochastic Cohen-Grossberg-type BAM neural networks with mixed delays. By utilizing the Lyapunov-Krasovskii functional and the linear matrix inequality (LMI) approach, some sufficient LMI-based conditions are obtained to guarantee the global asymptotic stability of sto
✦ LIBER ✦
An LMI approach to global asymptotic stability of the delayed Cohen–Grossberg neural network via nonsmooth analysis
✍ Scribed by Wenwu Yu; Jinde Cao; Jun Wang
- Publisher
- Elsevier Science
- Year
- 2007
- Tongue
- English
- Weight
- 472 KB
- Volume
- 20
- Category
- Article
- ISSN
- 0893-6080
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This paper deals with the problem of global exponential stability for a general class of stochastic high-order neural networks with mixed time delays and Markovian jumping parameters. The mixed time delays under consideration comprise both discrete time-varying delays and distributed time-delays. Th