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This paper solves the problem of delay-dependent H2 guaranteed cost control for singular stochastic neural networks with distributed delays. Parameter uncertainties are norm-bounded. The time-delay factors are unknown and time-varying with known bounds. The aim of this paper is to prove neural networks are stochastically asymptotically stable in the means quare for all admissible parameter uncertainties...
In this technical note, the globally exponential stabilization problem is investigated for a general class of stochastic systems with both Markovian jumping parameters and mixed time-delays. The mixed mode-dependent time-delays consist of both discrete and distributed delays. We aim to design a memoryless state feedback controller such that the closed-loop system is stochastically exponentially stable...
The global robust exponential stability in mean square for a class of stochastic neural networks with distributed delays and polytopic uncertainties is investigated in this paper. Parameter-dependent Lypaunov-Krasovskii functionals and free-weighting matrices are employed to obtain sufficient condition that guarantee the robust global exponential stability the considered stochastic neural networks...
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