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On the computational power of neural nets

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Published:01 July 1992Publication History

ABSTRACT

This paper deals with finite networks which consist of interconnections of synchronously evolving processors. Each processor updates its state by applying a “sigmoidal” scalar nonlinearity to a linear combination of the previous states of all units. We prove that one may simulate all Turing Machines by rational nets. In particular, one can do this in linear time, and there is a net made up of about 1,000 processors which computes a universal partial-recursive function. Products (high order nets) are not required, contrary to what had been stated in the literature. Furthermore, we assert a similar theorem about non-deterministic Turing Machines. Consequences for undecidability and complexity issues about nets are discussed too.

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          cover image ACM Conferences
          COLT '92: Proceedings of the fifth annual workshop on Computational learning theory
          July 1992
          452 pages
          ISBN:089791497X
          DOI:10.1145/130385

          Copyright © 1992 ACM

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          • Published: 1 July 1992

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