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This paper presents the delay-dependent $$H_\infty$$ H ∞ and generalized H 2 filters design for stochastic neural networks with time-varying delay and noise disturbance. The stochastic neural networks under consideration are subject to time-varying delay in both the state and measurement equations. The aim is to design a stable full-order linear filter(More)
This paper is concerned with the asymptotical stability analysis for stochastic static neural networks with time-varying delay. Here, the time derivative of the time-varying delay is no longer required to be smaller than one. With the use of convex polyhedron method, by constructing appropriate Lyapunov-Krasovskii functional, several delay-dependent(More)
The problem of robust L<sub>2</sub>-L<sub>&#x221E;</sub> filter design of uncertain neutral stochastic systems with Markovian jumping parameters and time delay is discussed in this paper. The parameter uncertainties are assumed to be norm-bounded. Based on the Lyapunov-krasovskii theory and generalized Finsler lemma, a delay-dependent stability condition is(More)
This paper concerns the design of the non-fragile H<sub>&#x221E;</sub> filter for the fuzzy system with time-varying delays. Attention is focused on the design of the filter which is subject to gain variations, such that the filtering system is robustly stable with a prescribed H<sub>&#x221E;</sub> performance level for all admissible uncertainties. A(More)
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