Robust Exponential Stability of Stochastic Discrete-Time BAM Neural Networks with Markovian Jumping Parameters and Delays
2014 ◽
Vol 989-994
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pp. 1877-1882
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Keyword(s):
The problem of robustly globally exponential stability in the mean square is investigated for stochastic uncertain discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays and Markovian jumping parameters. The uncertainties are assumed to be the linear fractional form. By using Lyapunov-Krasovskii functional (LKF) method and some novel technique, a delay-dependent exponential stability criterion is established in terms of linear matrix inequalities (LMIs). A numerical example is provided to show the effectiveness and the improvement of the proposed methods.
2012 ◽
Vol 546-547
◽
pp. 772-777
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Delay-Dependent Exponential Stability for Discrete-Time BAM Neural Networks with Time-Varying Delays
2008 ◽
Vol 2008
◽
pp. 1-14
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2014 ◽
Vol 69
(1-2)
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pp. 70-80
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Keyword(s):
2010 ◽
Vol 24
(9)
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pp. 760-785
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2012 ◽
Vol 349
(6)
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pp. 1972-1988
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Keyword(s):
Keyword(s):