Exponential p-stability of stochastic recurrent neural networks with mixed delays and Markovian switching

Exponential p-stability of stochastic recurrent neural networks with mixed delays and Markovian switching
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具有混合延迟和马尔可夫切换的随机循环神经网络的指数 p 稳定性

DOI:
10.1016/j.neucom.2012.09.026
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发表时间:
2013-03
期刊:
影响因子:
6
通讯作者:
Xu, Daoyi
Xu, Daoyi
中科院分区:
计算机科学2区
文献类型:
--
作者:
Li, Bing;Xu, Daoyi

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This paper is concerned with the stability analysis of stochastic recurrent neural networks with mixed delays and Markovian switching. By the properties of nonsingular M-matrix and stochastic analysis techniques, we establish a set of novel L-operator inequalities with finite modes and propose some sufficient criteria for ensuring the exponential p-stability of the equilibrium solution. The obtained results are new and improve the earlier publications. Two examples and simulations are given to demonstrate the efficiency of theoretical results.
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