Titlebook: Neural Networks; An Introduction Berndt Müller,Joachim Reinhardt Textbook 19901st edition Springer-Verlag Berlin Heidelberg 1990 Konnektion

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Coupled Neural Networksns. On the other hand, any general “recurrent” neural network can be considered to be represented by a feed-forward perceptron, albeit one with possibly very many layers. The reason for this strange equivalence is that the temporal evolution (3.5) of an arbitrary network constructed from binary neur

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Unsupervised Learningt has a number of rather unrealistic aspects, especially concerning the comparison with biological nerve nets. It is particularly troublesome in this respect: that complete knowledge of the deviation of the output from the desired reaction is required to determine the adjustment even of neurons in h

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Statistical Physics and Spin Glassestic system characterized by a lattice of discrete spin variables .. = ±1. Such systems are known under the name .. If the spin—spin interaction, i.e. the coupling coefficients .., extend over large distances and take on irregular values one speaks of a .. The peculiar properties of such spin glasses

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