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Analysis and design of asymmetric Hopfield networks with discrete-time dynamics

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Abstract

The retrieval properties of the asymmetric Hopfield neural networks (AHNNs) with discrete-time dynamics are studied in this paper. It is shown that the asymmetry degree is an important factor influencing the network dynamics. Furthermore, a strategy for designing AHNNs of different sparsities is proposed. Numerical simulations show that AHNNs can perform as well as symmetric ones, and the diluted AHNNs have the virtues of small wiring cost and high pattern recognition quality.

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Authors and Affiliations

  1. Institute of Systems Engineering, Tianjin University, Tianjin, 300072, China

    Pengsheng Zheng, Jianxiong Zhang & Wansheng Tang

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  1. Pengsheng Zheng
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  2. Jianxiong Zhang
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  3. Wansheng Tang
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Correspondence to Jianxiong Zhang.

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Zheng, P., Zhang, J. & Tang, W. Analysis and design of asymmetric Hopfield networks with discrete-time dynamics. Biol Cybern 103, 79–85 (2010). https://doi.org/10.1007/s00422-010-0391-9

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  • DOI: https://doi.org/10.1007/s00422-010-0391-9

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