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Saturday, April 18, 2020 | History

2 edition of Encyclopedia of Computer Science and Technology: Volume 12 - Pattern Recognition found in the catalog.

Encyclopedia of Computer Science and Technology: Volume 12 - Pattern Recognition

Structural Description Languages to Reliability of Computer Systems

by Jack Belzer

  • 272 Want to read
  • 30 Currently reading

Published by CRC .
Written in English

    Subjects:
  • Library & information services,
  • Questions & Answers,
  • Encyclopedias,
  • Reference,
  • General,
  • Library & Information Science,
  • Computers / General,
  • Computer science

  • The Physical Object
    FormatHardcover
    Number of Pages448
    ID Numbers
    Open LibraryOL8125221M
    ISBN 100824722620
    ISBN 109780824722623

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Encyclopedia of Computer Science and Technology: Volume 12 - Pattern Recognition by Jack Belzer Download PDF EPUB FB2

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Encyclopedia of Computer Science and Technology: Volume 12 - Pattern Recognition: Structural Description Languages to Reliability of Computer Systems (Encyclopedia of Computer Science & Technology) May 1, Encyclopedia of Computer Science and Technology: Volume 12 - Pattern Recognition: Structural Description Languages to Reliability of Computer Systems (Encyclopedia of Computer Science & Technology): ISBN ().

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The new Encyclopedia of Sustainable Technologies provides an authoritative assessment of the sustainable technologies that are currently available or in development.

Sustainable technology includes the scientific understanding, development and application of a wide range of technologies and processes and their environmental implications.

Journal of Computer and System Sciences, 56(2), (special issue on COLT`95). [ bib] [Bar98] P. Bartlett. The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network. IEEE Transactions on Information Theory, 44(2), [ bib] [BKP97].

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Warren McCulloch and Walter Pitts () opened the subject by creating a computational model for neural networks. In the late s, D. Hebb created a learning hypothesis based on the mechanism of neural plasticity that became known as Hebbian and Wesley A. Clark () first used computational machines, then called "calculators", to simulate a Hebbian network.

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