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A Matrix Algebra for Neural Nets

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Part of the book series: NATO Conference Series ((SYSC,volume 5))

Abstract

Almost thirty-five years ago in their classic paper, McCulloch and Pitts (1943) described a method for modeling the nervous system. The basic idea of McCulloch and Pitts’ paper is that the nervous system can be described as a finite set of elements, called neurons, that have only two states, “on” and “off,” They assumed that time could be quantized into a set of discrete instants, so that the state of a neuron at the next instant of time would be a function of the present states of the neurons (and external inputs) that impinged on it.

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References

  1. E.R. Caianiello, “Some remarks on the temorial linearization of general and linearly separable Boolean functions.” Kybernetik 12, 1973, pp. 90–93.

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  5. W.S. McCulloch and W.H. Pitts, “A logical calculus of the ideas immanent in nervous activity.” Bull. Math. Biophys. 5, 1943, pp. 115–133.

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© 1978 Springer Science+Business Media New York

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Cull, P. (1978). A Matrix Algebra for Neural Nets. In: Klir, G.J. (eds) Applied General Systems Research. NATO Conference Series, vol 5. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-0555-3_43

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  • DOI: https://doi.org/10.1007/978-1-4757-0555-3_43

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4757-0557-7

  • Online ISBN: 978-1-4757-0555-3

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