Nonlinearities in Artificial Neural Systems Interpreted as an Application of Ising Physics

In this review, the nonlinearities in different processes such as spin glasses, finite field models, Hamiltonian functions, learning and storing capabilities, mean field systems and others in the area of physics related to the artificial neural networks namely the main brain structure interpreted as Ising spin systems are discussed. It is shown that nonlinearities serve as exclusive role in the applied physics field.

Abstract licence: CC BY

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