Asymmetric Hopfield-type networks: theory and applications
Neural Networks
Stability conditions for discrete neural networks in partial simultaneous updating mode
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
IEEE Transactions on Neural Networks
New stability conditions for Hopfield networks in partial simultaneous update mode
IEEE Transactions on Neural Networks
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The stability of Discrete Hopfield neural networks (DHNNs) is very important in various applications, but stability analysis of complex DHNNs is difficult However, stability analysis of simple and small DHNNs is easy to obtain In this paper, we study on the stability of DHNNs combined with two small ones that maybe have partially or completely different neurons, and consider the connected weights of different neurons And some new stability conditions of the DHNNs are obtained by studying the stability of small ones Those results provide the guided significance for designing a DHNNs and afford benefit for stability analysis of DHNNs The obtained results provide some theory bases of the application of DHNNs.