Novel stability criteria for bidirectional associative memory neural networks with time delays

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)519-546
Journal / PublicationInternational Journal of Circuit Theory and Applications
Issue number5
Publication statusPublished - Sept 2002


In this paper, the bidirectional associative memory (BAM) neural network with axonal signal transmission delay is considered. This model is also referred to as a delayed dynamic BAM model. By combining a number of different Lyapunov functionals with the Razumikhin technique, some sufficient conditions for the existence of a unique equilibrium and global asymptotic stability of the network are derived. These results are fairly general and can be easily verified. Besides, the approach for the analysis allows one to consider several different types of activation functions, including piecewise linear sigmoids with bounded activations as well as C1-smooth sigmoids. It is believed that these results are significant and convenient in the design and applications of BAM neural networks. Copyright © 2002 John Wiley & Sons, Ltd.

Research Area(s)

  • Bidirectional associative memory, Global asymptotic stability, Lyapunov functional, Neural networks, Time delay