A Logical Calculus of Ideas Immanent in Nervous Activity

Looking for more research papers to read, I scanned my Hands-On Machine Learning notes for the many papers that were referenced there. This is one of those papers. These papers are mainly on machine learning and deep learning topics.

Reference A Logical Calculus of Ideas Immanent in Nervous Activity Paper

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Introduction

Because of the ”all-or-none” character of nervous activity, neural events and the relations among them can be treated by means of propositional logic. It is found that the behavior if every net can be described in these terms, with the addition of more complicated logical means for nets containing circles; and that for any logical expression satisfying certain conditions, one can find a net behaving in the fashion it describes.

The nervous system is a set of neurons, each having a soma and an axon. Their adjustments, or synapses, are always between the axon of one neuron and the soma of another. At any instanct a neuron has some threshold, which excitation must exceed to initiate an imulse.

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