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Effects of global perturbations on learning capability in a CMOS analogue implementation of synchronous Boltzmann machine

  • Kurosh Madani
  • Ghislain de Tremiolles
Artificial Neural Nets Simulation and Implementation
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1607)

Abstract

All of the presented implementations of Artificial Neural Networks (A.N.N.) have been supposed to be working in ideal conditions, however, real applications will be subject to local and global perturbations. Since 1994, we have investigated the behaviour modelling of electronic A.N.N. with global perturbation conditions. We have scrutinised the behaviour analysis of a CMOS analogue implementation of synchronous Boltzmann Machine model with both ambient temperature and electrical perturbation. In this paper we present, using our model, the analysis of these global perturbations effects on learning capability of the above mentioned CMOS based analogue implementation. Simulation and experimental results have been exposed validating our concepts.

Key Words

Global Perturbations Neural network Learning capability Modelling Experimental validation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Kurosh Madani
    • 1
  • Ghislain de Tremiolles
    • 1
  1. 1.Division Réseaux NeuronauxLeriss-Université Paris XII, I.U.T. De SenartLieusaintFrance

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