Neural networks and physical systems with emergent collective computational abilities
- Creators
- Hopfield, J. J.
Abstract
Computational properties of use to biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or neurons). The physical meaning of content-addressable memory is described by an appropriate phase space flow of the state of a system. A model of such a system is given, based on aspects of neurobiology but readily adapted to integrated circuits. The collective properties of this model produce a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size. The algorithm for the time evolution of the state of the system is based on asynchronous parallel processing. Additional emergent collective properties include some capacity for generalization, familiarity recognition, categorization, error correction, and time sequence retention. The collective properties are only weakly sensitive to details of the modeling or the failure of individual devices.
Additional Information
© 1982 by the National Academy of Sciences. Contributed by John J. Hopfield, January 15, 1982. The work at California Institute of Technology was supported in part by National Science Foundation Grant DMR-8107494. This is contribution no. 6580 from the Division of Chemistry and Chemical Engineering. The publication costs of this article were defrayed in part by page charge payment. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. §1734 solely to indicate this fact.Files
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Additional details
- Eprint ID
- 7427
- Resolver ID
- CaltechAUTHORS:HOPpnas82
- Created
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2007-02-13Created from EPrint's datestamp field
- Updated
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2019-10-02Created from EPrint's last_modified field