DELAY-DEPENDENT GLOBAL ROBUST ASYMPTOTIC STABILITY ANALYSIS OF BAM NEURAL NETWORKS WITH TIME DELAY: AN LMI APPROACH

Xu-Yang Lou () and Bao-Tong Cui ()
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Xu-Yang Lou: Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Rd., Wuxi, Jiangsu 214122, P.R. China
Bao-Tong Cui: Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Rd., Wuxi, Jiangsu 214122, P.R. China

New Mathematics and Natural Computation (NMNC), 2007, vol. 03, issue 01, 57-68

Abstract: 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.

Keywords: Bi-directional associative memory neural networks; delay; robust asymptotic stability; linear matrix inequality; Lyapunov-Krasovskii functional (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1142/S1793005707000628

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