Programming a massively parallel, computation universal system: static behavior

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In previous work by the authors, the ''optimum finding'' properties of Hopfield neural nets were applied to the nets themselves to create a ''neural compiler.'' This was done in such a way that the problem of programming the attractors of one neural net (called the Slave net) was expressed as an optimization problem that was in turn solved by a second neural net (the Master net). In this series of papers that approach is extended to programming nets that contain interneurons (sometimes called ''hidden neurons''), and thus deals with nets capable of universal computation. 22 refs.

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Pages: 26

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Lapedes, A. & Farber, R. January 1, 1986.

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Description

In previous work by the authors, the ''optimum finding'' properties of Hopfield neural nets were applied to the nets themselves to create a ''neural compiler.'' This was done in such a way that the problem of programming the attractors of one neural net (called the Slave net) was expressed as an optimization problem that was in turn solved by a second neural net (the Master net). In this series of papers that approach is extended to programming nets that contain interneurons (sometimes called ''hidden neurons''), and thus deals with nets capable of universal computation. 22 refs.

Physical Description

Pages: 26

Notes

NTIS, PC A03/MF A01.

Source

  • Neural nets and computation conference, Snowbird, UT, USA, 1 Apr 1986

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  • Other: DE86010171
  • Report No.: LA-UR-86-1179
  • Report No.: CONF-8604173-1
  • Grant Number: W-7405-ENG-36
  • Office of Scientific & Technical Information Report Number: 5627833
  • Archival Resource Key: ark:/67531/metadc1084519

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Office of Scientific & Technical Information Technical Reports

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  • January 1, 1986

Added to The UNT Digital Library

  • Feb. 10, 2018, 10:06 p.m.

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  • May 30, 2018, 12:22 p.m.

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Lapedes, A. & Farber, R. Programming a massively parallel, computation universal system: static behavior, article, January 1, 1986; New Mexico. (digital.library.unt.edu/ark:/67531/metadc1084519/: accessed November 18, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.