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A Formal Model of Neuron That Provides Consistent Predictions

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 196)

Abstract

We define maximal specific rules that avoid the problem of statistical ambiguity and provide predictions with maximum conditional probability. Also we define a special semantic probabilistic inference that learn these maximal specific rules and may be considered as a special case of Hebbian learning. This inference we present as a formal model of neuron and prove that this model provides consistent predictions.

Keywords

neuron formal model Hebbian learning probabilistic inference 

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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Sobolev Institute of Mathematics of the Siberian Branch of the Russian Academy of SciencesNovosibirsk State UniversityOblastRussia

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