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The Hamilton neural network model

Author

Listed:
  • Shuai, J.W.
  • Chen, Z.X.
  • Liu, R.T.
  • Wu, B.X.

Abstract

In this paper, the Dirac symbol is used to represent a neural network, and a discrete Hamilton neural network model with a 16-state (± 1 ± i ± j ± k) neuron has been presented. By using signal-to-noise theory and computer numerical simulation, the stability, the storage capacity and the error correction ability of the model are analysed. The storage capacity ratio of the presented model equals that of the Hopfield model. This 16-state neural network can be applied to recognize 16-level gray or color patterns.

Suggested Citation

  • Shuai, J.W. & Chen, Z.X. & Liu, R.T. & Wu, B.X., 1995. "The Hamilton neural network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 216(1), pages 20-31.
    • Handle: RePEc:eee:phsmap:v:216:y:1995:i:1:p:20-31
    DOI: 10.1016/0378-4371(94)00244-N
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    References listed on IDEAS

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    1. Dotsenko, V.S. & Tirozzi, B., 1992. "Replica-symmetry breaking in neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 185(1), pages 385-394.
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    Cited by:

    1. Zheng, Jin-Cheng & Chen, Jian-Yong & Shuai, Jian-Wei & Cai, Shu-Hui & Wang, Ren-zhi, 1997. "Storage capacity of the Hopfield neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 313-319.
    2. Zhenxiang Chen, & Jianwei Shuai, & Jincheng Zheng, & Riutang Liu, & Wu, Boxi, 1996. "The storage capacity of the complex phasor neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 225(2), pages 157-163.
    3. Shuai, J.W. & Zheng, J.C. & Chen, Z.X. & Liu, R.T. & Wu, B.X., 1997. "The three-dimensional rotation neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 238(1), pages 23-38.

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