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Models of Large Networks: Computer-Oriented Approaches

  • Ronald J. MacGregor
  • Edwin R. Lewis

Abstract

This chapter takes up the second mainstream of modeling techniques for large neural networks—those that make extensive use of large-scale digital computers or particularly lend themselves to realization on large-scale computers. A germinal source work which has greatly influenced much subsequent work in this area was published in 1943 by McCulloch and Pitts. This paper has been extremely influential in propagating the so-called automata-theoretic view of neural-network dynamics which has been taken over, or at least influenced, by many analytically oriented researchers as well, as we saw in the previous chapter. In this chapter we discuss this basic source paper, its ramifications, and several contemporary examples of computer-oriented approaches to large neural networks.

Keywords

Neuronal Network Cyclic Mode Sequential Machine Cyclic Activity Neural Code 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Plenum Press, New York 1977

Authors and Affiliations

  • Ronald J. MacGregor
    • 1
  • Edwin R. Lewis
    • 2
  1. 1.University of ColoradoBoulderUSA
  2. 2.University of CaliforniaBerkeleyUSA

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