By George A. Anastassiou (auth.)
This short monograph is the 1st one to deal completely with the quantitative approximation via man made neural networks to the identity-unit operator. right here we examine with charges the approximation houses of the "right" sigmoidal and hyperbolic tangent man made neural community confident linear operators. particularly we research the measure of approximation of those operators to the unit operator within the univariate and multivariate instances over bounded or unbounded domain names. this can be given through inequalities and with using modulus of continuity of the concerned functionality or its greater order spinoff. We study the true and complicated cases.
For the benefit of the reader, the chapters of this booklet are written in a self-contained style.
This treatise is determined by author's final years of comparable examine work.
Advanced classes and seminars could be taught out of this short publication. All worthwhile heritage and motivations are given in line with bankruptcy. A comparable checklist of references is given additionally in line with bankruptcy. The uncovered effects are anticipated to discover functions in lots of components of laptop technological know-how and utilized arithmetic, akin to neural networks, clever structures, complexity concept, studying thought, imaginative and prescient and approximation thought, and so on. As such this monograph is appropriate for researchers, graduate scholars, and seminars of the above topics, additionally for all technological know-how libraries.
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