Paper Title:
Exponential Convergence Rate Estimation for a Class of BAM Neural Networks with Time-Delays
  Abstract

This paper is concerned with the exponential stability analysis problem for a class of neutral bidirectional associative memory (BAM) neural networks with parameter uncertainties and mixed time-delays where the parameter uncertainties are norm-bounded and the mixed time-delays involve discrete, distributed and neutral time-delays. By utilizing free-weighting matrix method and an appropriately constructed Lyapunov-Krasovskii Functional, some nove delay-dependent and decay-rate dependent exponential stability criteria are derived in the terms of linear matrix inequalities (LMIs). Meanwhile, the maximum allowable decay rate can be estimated based on the obtained results. Two numerical examples are presented to demonstrate the effectiveness of the proposed method.

  Info
Periodical
Advanced Materials Research (Volumes 143-144)
Edited by
H. Wang, B.J. Zhang, X.Z. Liu, D.Z. Luo, S.B. Zhong
Pages
707-711
DOI
10.4028/www.scientific.net/AMR.143-144.707
Citation
J. D. Yu, "Exponential Convergence Rate Estimation for a Class of BAM Neural Networks with Time-Delays", Advanced Materials Research, Vols. 143-144, pp. 707-711, 2011
Online since
October 2010
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