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In this paper, the problem of asymptotic stability for stochastic Hopfield neural networks (HNNs) with time delays is investigated. New delay-dependent stability criteria are presented by constructing a novel Lyapunov-Krasovskii functional. Moreover, the results are further extended to the delayed stochastic HNNs with parameter uncertainties. The main idea(More)
This brief addresses the stability analysis problem for stochastic neural networks (SNNs) with discrete interval and distributed time-varying delays. The interval time-varying delay is assumed to satisfy 0 &lt; d<sub>1</sub> ¿ d(t) ¿ d<sub>2</sub> and is described as <i>d</i>(<i>t</i>) = <i>d</i> <sub>1</sub>+<i>h</i>(<i>t</i>) with 0 ¿ <i>h</i>(<i>t</i>) ¿(More)
This paper deals with the problem of feedback control for networked systems with discrete and distributed delays subject to quantization and packet dropout. Both a state feedback controller and an observer-based output feedback controller are designed. The infinite distributed delay is introduced in the discrete networked domain for the first time. Also, it(More)
This paper is focused on the problem of H∞ filtering for a class of discrete-time T-S fuzzy time-varying delay systems. Our interest is how to design fulland reducedorder filters that guarantee the filtering error system to be asymptotically stable with a prescribed H∞ performance. Sufficient conditions for the obtained filtering error system are proposed(More)
In this paper, the problem of induced &#x2113;<sub>2</sub> filter design is investigated for a class of T-S fuzzy Ito stochastic systems. A novel comparison model is introduced by employing a new approximation for time-varying delay state, and then sufficient conditions are proposed for the resulting filtering error system. The desired filter is to be(More)