4.7 Article

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

Journal

COMPUTERS & MATHEMATICS WITH APPLICATIONS
Volume 62, Issue 4, Pages 1838-1861

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.camwa.2011.06.027

Keywords

BAM neural networks; Fuzzy systems; Markovian jumping parameters; Impulses; Neutral delay

Funding

  1. UGC-SAP (DRS-II), Government of India, New Delhi [F.510/2/DRS/2009 (SAP-I)]

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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 (LKEs) 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. (C) 2011 Elsevier Ltd. All rights reserved.

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