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Adaptive models in neural networks

  • Panos A. Ligomenides
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 686)

Abstract

Artificial neural networks (ANNs) are principally attractive for their high degree of parallelism, for their associative memory properties, and for their ability to swiftly compute “near-optimal” solutions to highly constrained optimization problems. In this paper we examine the essential adaptive models that have been proposed for ANNs.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Panos A. Ligomenides
    • 1
  1. 1.Cybernetics Research Lab., Electrical Eng. Dept.University of MarylandCollege Park

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