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Exponential p-stability of impulsive stochastic Cohen–Grossberg neural networks with mixed delays

✍ Scribed by Xiaohu Wang; Qingyi Guo; Daoyi Xu

Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
204 KB
Volume
79
Category
Article
ISSN
0378-4754

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✦ Synopsis

In this paper, we study the impulsive stochastic Cohen-Grossberg neural networks with mixed delays. By establishing an Loperator differential inequality with mixed delays and using the properties of M-cone and stochastic analysis technique, we obtain some sufficient conditions ensuring the exponential p-stability of the impulsive stochastic Cohen-Grossberg neural networks with mixed delays. These results generalize a few previous known results and remove some restrictions on the neural networks. Two examples are also discussed to illustrate the efficiency of the obtained results.

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Exponential stability of Cohen–Grossberg
Exponential stability of Cohen–Grossberg neural networks with delays
✍ Xiaofeng Liao; Jiyun Yang; Songtao Guo 📂 Article 📅 2008 🏛 Elsevier Science 🌐 English ⚖ 169 KB

The exponential stability characteristics of the Cohen-Grossberg neural networks with discrete delays are studied in this paper, without assuming the symmetry of connection matrix as well as the monotonicity and differentiability of the activation functions and the self-signal functions. By construc