Delay-dependent exponential stability of discrete-time bam neural networks with time varying delays

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Abstract

In this paper, the global exponential stability is discussed for discrete-time bidirectional associative memory (BAM) neural networks with time varying delays. By the linear matrix inequality (LMI) technique and discrete Lyapunov functional combined with inequality techniques, a new global exponential stability criterion of the equilibrium points is obtained for this system. The proposed result is less restrictive than those given in the earlier literatures, and easier to check in practice. Remarks are made with other previous works to show the superiority of the obtained results, and the simulation example is used to demonstrate the effectiveness of our result. © 2009 Springer Berlin Heidelberg.

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APA

Zhang, R., Wang, Z., Feng, J., & Jing, Y. (2009). Delay-dependent exponential stability of discrete-time bam neural networks with time varying delays. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5551 LNCS, pp. 440–449). https://doi.org/10.1007/978-3-642-01507-6_51

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