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Increasing the Biological Inspiration of Neural Networks

  • Francesco E. Lauria
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2486)

Abstract

Starting from a nerve cell functional characterization, we define formally the autonomous learning to concatenate sequences and prove it to be a possible solution for the problem that faces the, eg vertebrate, nervous systems: ie, to choose and to store, without outside help, the instructions to compute the actual sensor/effector correspondences they have to control. In our formal system we assign the initial connection matrix elements so that the rules, namely the Caianiello relation iterated application, autonomously and deterministically control the meta-rule, namely the Hebbian rule, application.

Keywords

Autonomus learning Concatenate sequences Caianiello model Hebbian rule 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Francesco E. Lauria
    • 1
  1. 1.Dipartimento di Scienze FisicheUniversit gravea di Napoli Federico II & INFM Complesso Universitario di Monte Sant’AngeloNapoliItaly (EU)

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