Abstract
The stability of recurrent neural networks is known to be bases of successful applications of the networks. Discrete Hopfield neural networks with delay are extension of discrete Hopfield neural networks without delay. In this paper, the stability of discrete Hopfield neural networks with delay is mainly investigated. The method, which does not make use of energy function, is simple and valid for the dynamic behavior analysis of the neural networks with delay. Several new sufficient conditions for the networks with delay converging towards a limit cycle with length 2 are obtained. All results established here generalize the existing results on the stability of both discrete Hopfield neural networks without delay and with delay in parallel updating mode.
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Ma, R., Lei, S., Zhang, S. (2005). Dynamic Behavior Analysis of Discrete Neural Networks with Delay. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_40
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DOI: https://doi.org/10.1007/11427391_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25912-1
Online ISBN: 978-3-540-32065-4
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