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This paper investigates the reliable mixed passive and H 1 filtering problem for uncertain semi-Markov jump delayed systems subject to sensor failures. The parameter uncertainties are randomly occurring with two stochastic variables, which are mutually independent and satisfy certain probabilistic distributions on the interval OE0; 1. The objective is to focus on the design of a reliable filter ensuring the mixed passivity and H 1 performance level of the resulting filtering error system in the presence of sensor failures. By using an improved reciprocally convex approach combined with a novel integral inequality, sufficient conditions of mixed passivity and H 1 performance analysis for the considered systems are derived. Based on these, a desired reliable filter design method is developed, and the parameters of the filter are readily calculated by employing a simple expression of the desired filter. Three numerical examples are presented to demonstrate the effectiveness and the reduced conservatism of the proposed method. RELIABLE MIXED PASSIVE AND H 1 FILTERING 3233 To simplify the notation, we denote A i D A .t/ for each .t/ D i 2 S, and the other symbols are similarly denoted. In (1)-(4), the continuous function .t/ denotes the time-varying delay of the system that satisfies 0 < .t/ 6 and P .t/ 6 ; '.t/ is a vector-valued initial continuous function defined on the interval OE ; 0. In the sequel, A i , A 1i , B i , C i , D i , and L i are known real constant

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This paper is concerned with the problem of extended dissipativity-based state estimation for discrete-time Markov jump neural networks (NNs), where the variation of the piecewise time-varying transition probabilities of Markov chain is subject to a set of switching signals satisfying an average dwell-time property. The communication links between the NNs and the estimator are assumed to be imperfect, where the phenomena of signal quantization and data packet dropouts occur simultaneously. The aim of this paper is to contribute with a Markov switching estimator design method, which ensures that the resulting error system is extended stochastically dissipative, in the simultaneous presences of packet dropouts and signal quantization stemmed from unreliable communication links. Sufficient conditions for the solvability of such a problem are established. Based on the derived conditions, an explicit expression of the desired Markov switching estimator is presented. Finally, two illustrated examples are given to show the effectiveness of the proposed design method.

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