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Architectures for Optical Neural Networks

  • Chapter
Nonlinear Optics in Signal Processing

Part of the book series: Engineering Aspects of Lasers Series ((EALS,volume 49))

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Abstract

Artificial neural networks are parallel processing systems which have applications in speech and pattern recognition (Rumelhart and McCelland, 1986; Prager et al., 1986; Lippmann, 1987; Szu, 1986; Geman and Geman, 1984; Luttrell, 1985; Widrow et al. 1988), function optimization (Geman and Geman, 1984; Barhen et al., 1987; Hinton et al., 1984; Kirkpatrick et al., 1983; Hopfield and Tank, 1986), robotics (Barhen et al., 1987), and control (Psaltis et al., 1988a). They consist of a set of identical, nonlinear processing elements, generically known as neurons, which are linked together to form a highly interconnected network. Information is represented by the pattern of activity of the neurons and data are stored by distributing them throughout the network’s connections. This is done by weighting the links with positive and negative values to indicate the effect that one neuron has on another. This makes the system fault tolerant since each neuron is connected to many others and each weight represents the ‘average’ stimulus over the data set, so the loss of a few connections does not drastically affect the operation of the network.

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Authors
  1. Ashley J. Bostel
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  2. Andrew K. Powell
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  3. Trevor J. Hall
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Editor information

Editors and Affiliations

  1. University of Southampton, UK

    Robert W. Eason (Senior Lecturer in Optics) (Senior Lecturer in Optics)

  2. Center for Research in Electro-Optics and Lasers, University of Central Florida, Orlando, USA

    Alan Miller (Professor of Physics and Electrical Engineering) (Professor of Physics and Electrical Engineering)

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© 1993 Springer Science+Business Media Dordrecht

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Bostel, A.J., Powell, A.K., Hall, T.J. (1993). Architectures for Optical Neural Networks. In: Eason, R.W., Miller, A. (eds) Nonlinear Optics in Signal Processing. Engineering Aspects of Lasers Series, vol 49. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-1560-5_7

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  • DOI: https://doi.org/10.1007/978-94-011-1560-5_7

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-4681-7

  • Online ISBN: 978-94-011-1560-5

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