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A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
Published on: May 25, 2019
Stability analysis of switched stochastic neural networks with time-varying delays
Xiaotai Wu1, Yang Tang2, Wenbing Zhang3
1School of Mathematics, Anhui Polytechnic University, Wuhu 241000, PR China.
Abstract:
This paper is concerned with the global exponential stability of switched stochastic neural networks with time-varying delays. Firstly, the stability of switched stochastic delayed neural networks with stable subsystems is investigated by utilizing the mathematical induction method, the piecewise Lyapunov function and the average dwell time approach. Secondly, by utilizing the extended comparison principle from impulsive systems, the stability of stochastic switched delayed neural networks with both stable and unstable subsystems is analyzed and several easy to verify conditions are derived to ensure the exponential mean square stability of switched delayed neural networks with stochastic disturbances. The effectiveness of the proposed results is illustrated by two simulation examples.
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