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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 30, Iss. 2 — Jan. 10, 1991
  • pp: 195–200

Hopfield model with multistate neurons and its optoelectronic implementation

Wei Zhang, Kazuyoshi Itoh, Jun Tanida, and Yoshiki Ichioka  »View Author Affiliations


Applied Optics, Vol. 30, Issue 2, pp. 195-200 (1991)
http://dx.doi.org/10.1364/AO.30.000195


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Abstract

A Hopfield model with multistate neurons is described. This model is able to deal with multivalued problems such as restoring a degraded image with gray level equivalent to that produced by the two-states model, but needs many less neurons and interconnections. The performance of this model is compared with that of the linear model, and it is concluded that the multistate neuron model can produce convergence more quickly. Finally, a hybrid system for the implementation of this model is discussed.

© 1991 Optical Society of America

History
Original Manuscript: January 2, 1990
Published: January 10, 1991

Citation
Wei Zhang, Kazuyoshi Itoh, Jun Tanida, and Yoshiki Ichioka, "Hopfield model with multistate neurons and its optoelectronic implementation," Appl. Opt. 30, 195-200 (1991)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-30-2-195


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References

  1. J. J. Hopfield, D. W. Tank, “Neural Computation of Decisions in Optimization Problems,” Biol. Cybern. 52, 141–152 (1985). [PubMed]
  2. M. Takeda, J. W. Goodman, “Neural Networks For Computation: Number Representations and Programming Complexity,” Appl. Opt. 25, 3033–3046 (1986). [CrossRef] [PubMed]
  3. Y.-T. Zhou, R. Chellappa, A. Vaid, K. Jenkins, “Image Restoration Using a Neural Network,” IEEE Trans. Acoust. Speech Signal Process, ASSP-36, 1141–1151 (1988). [CrossRef]
  4. G. Y. Sirat, A. D. Maruani, R. C. Chevallier, “Grey Level Neural Networks,” Appl. Opt. 28, 414–415 (1989). [CrossRef] [PubMed]
  5. D. W. Tank, J. J. Hopfield, “Simple Neural Optimization Networks: an A/D Converter, Signal Decision Circuit, and a Linear Programming Circuit,” IEEE Trans. Circuits Syst. CAS-33, 533–541 (1986). [CrossRef]
  6. E. Barnard, D. Casasent, “New Optical Neural System Architectures and Applications,” Proc. Soc. Photo-Opt. Instrum. Eng. 963, 537–544 (1988).
  7. E. Aarts, J. Korst, Simulated Annealing and Boltzmann Machines (Wiley, New York1989).
  8. D. E. Rumelhart et al., Parallel Distributed Processing (MIT press, Cambridge, 1986).
  9. N. H. Farhat, D. Psaltis, A. Prata, E. Paek, “Optical Implementation of the Hopfield Model,” Appl. Opt. 24, 1469–1475 (1985). [CrossRef] [PubMed]
  10. J. Ohta, S. Tai, M. Oita, K. Koroda, K. Kyuma, K. Hamaraka, “Optical Implementation of an Associative Neural Network Model With a Stochastic Process,” Appl. Opt. 28, 2426–2428 (1989). [CrossRef] [PubMed]
  11. E. Barnard, D. Casasent, “Optical Neural Net for Matrix Inversion,” Appl. Opt. 28, 2499–2504 (1989). [CrossRef] [PubMed]

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