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This paper is concerned with the distributed sampled-data H∞ state estimation problem for a class of discrete time-invariant systems over sensor networks. The plant under consideration is sampled with a fast period. The sampling intervals of the measurements are integer multiples of the fast period and the sampling processing is characterized by a Markov chain. In order to estimate the plant state,...
This paper is concerned with the finite-horizon H∞ state estimation problem for time-varying complex networks with redundant channels. The redundant channels are employed in the data transmission to against the fragility of communication networks commonly configured by the single channel subject to data missing and uniform quantization effects. The aim of the addressed problem is to design an estimator...
In this paper, the state estimation problem is investigated for a class of discrete-time stochastic neural networks with event-triggered transmission (ETT) mechanism. Different from the traditional periodic communication mechanism, the ETT mechanism employed in this paper possesses the advantage of mitigating the network traffic resulting from the unnecessary sending and receiving data between the...
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