DELAY-DEPENDENT GLOBAL ROBUST ASYMPTOTIC STABILITY ANALYSIS OF BAM NEURAL NETWORKS WITH TIME DELAY: AN LMI APPROACH
The global robust asymptotic stability of bi-directional associative memory (BAM) neural networks with constant or time-varying delays is studied. An approach combining the Lyapunov-Krasovskii functional with the linear matrix inequality (LMI) is taken to study the problem. Some a criteria for the global robust asymptotic stability, which gives information on the delay-dependent property, are derived. Some illustrative examples are given to demonstrate the effectiveness of the obtained results.
Year of publication: |
2007
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Authors: | LOU, XU-YANG ; CUI, BAO-TONG |
Published in: |
New Mathematics and Natural Computation (NMNC). - World Scientific Publishing Co. Pte. Ltd., ISSN 1793-7027. - Vol. 03.2007, 01, p. 57-68
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Publisher: |
World Scientific Publishing Co. Pte. Ltd. |
Subject: | Bi-directional associative memory neural networks | delay | robust asymptotic stability | linear matrix inequality | Lyapunov-Krasovskii functional |
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