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Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods
This book provides theoretical and practical knowledge for develop ment of algorithms that infer linear and nonlinear models. It offers a methodology for inductive learning of polynomial neural network mod els from data. The design of such tools contributes to better statistical data modelling when addressing tasks from various areas like system identification, chaotic tim ...more
Hardcover, 316 pages
Published May 1st 2006 by Springer
(first published January 1st 2006)
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