Titlebook: Neural Networks and Analog Computation; Beyond the Turing Li Hava T. Siegelmann Book 1999 Birkhäuser Boston 1999 Natur.Theorie.complexity.c

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Networks with Rational Weights,et of rationals. In contrast to the case described in the previous chapter, where we dealt only with integer weights, and each neuron could assume two values only, here a neuron can take on countably infinite different values. The analysis of networks with rational weights is a prerequisite for the

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Networks with Real Weights,l practical purposes, useless since systems with infinitely precise constants cannot be built. However, the real weights are appealing for the . modeling of analog computation that occurs in nature, as discussed in Chapter 2. In nature, the fact that the constants are not known to us, or cannot even

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The Model,In this chapter we introduce the formal model of the neural network to be utilized and analyzed in this book.

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Generalized Processor Networks,Up to this point we have analyzed in detail the computational properties of the analog recurrent neural network. From here on we turn to consider more general models of analog computation, and place our network within this wider framework.