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Robust stability of uncertain fuzzy BAM neural networks of neutral-type with Markovian jumping parameters and impulses. (English) Zbl 1231.34139
Summary: 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.
MSC:
34K36Fuzzy functional-differential equations
92B20General theory of neural networks (mathematical biology)
34K20Stability theory of functional-differential equations
34K50Stochastic functional-differential equations
Software:
Matlab
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