In this paper, the global exponential stability for a class of reaction-diffusion delayed bidirectional associate memory (BAM) neural networks with Dirichlet boundary conditions is addressed by using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium point of such networks are established. Finally, an example is given to show the effectiveness of the obtained result. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Fu, C., & Wu, A. (2009). Global exponential stability of reaction-diffusion delayed bam neural networks with dirichlet boundary conditions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5551 LNCS, pp. 303–312). https://doi.org/10.1007/978-3-642-01507-6_36
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