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Title of Journal: Neural Comput Applic

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Abbravation: Neural Computing and Applications

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Springer London

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DOI

10.1007/s00202-006-0046-y

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ISSN

1433-3058

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Robust dissipativity and passivity based state est

Authors: G Nagamani S Ramasamy Anke MeyerBaese
Publish Date: 2015/11/30
Volume: 28, Issue: 4, Pages: 717-735
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Abstract

In this paper the problem of robust state estimation for discretetime stochastic Markov jump neural networks with discrete and distributed timevarying delays is investigated based on dissipativity and passivity theory The parameters of the neural networks are subject to the switching from one mode to another according to a Markov chain By using the Lyapunov–Krasovskii functional together with linear matrix inequality approach a new set of sufficient conditions are derived for the existence of state estimator such that the error state system is strictly mathcal Q mathcal S mathcal Rgamma dissipative Finally numerical examples are addressed to show the effectiveness of the proposed design method

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