Robust stability of uncertain fuzzy BAM neural networks of neutral-type with Markovian jumping parameters and impulses

Robust stability of uncertain fuzzy BAM neural networks of neutral-type with Markovian jumping parameters and impulses

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Article ID: iaor20118234
Volume: 62
Issue: 4
Start Page Number: 1838
End Page Number: 1861
Publication Date: Aug 2011
Journal: Computers and Mathematics with Applications
Authors: ,
Keywords: neural networks, markov processes
Abstract:

In this paper, the problem of neutral‐type impulsive bidirectional associative memory neural networks (NIBAMNNs) with time delays are first established by a Takagi–Sugeno (T‐S) fuzzy model in which the consequent parts are composed of a set of NIBAMNNs with interval delays and Markovian jumping parameters (MJPs). Sufficient conditions to check the robust exponential stability of the derived model are based on the Lyapunov–Krasovskii functionals (LKFs) containing some novel triple integral terms, Lyapunov stability theory and employing the free‐weighting matrix method. The delay‐dependent stability conditions are established in terms of linear matrix inequalities (LMIs), which can be very efficiently solved using Matlab LMI control toolbox. Finally, numerical examples and remarks are given to illustrate the effectiveness and usefulness of the derived results.

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