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Identification, Adaptation, Learning
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Identification, Adaptation, Learning

The Science of Learning Models from Data
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Description

This book offers a tutorial view of recent trends in the science of modelling, adaptation, and learning. The most important modern approaches to identification, namely the stochastic, behavioral, subspace, and frequency domain approaches, are discussed thoroughly. On adaptation, tuning the parameters of a linear model is presented as a cure for uncertainty, and the asymptotics of recursive least squares and self-tuning systems are explained simply after a fully deterministic analysis. For constructing nonlinear models from data, neural networks and wavelets are considered as useful nonlinear tools, and fuzzy logic is presented as a way of coping with qualitative information. A final chapter deals with optimization methods. The book will become an important reference for researchers in the field.
Release date Australia
December 9th, 2010
Audience
  • Professional & Vocational
Contributors
  • Edited by Giorgio Picci
  • Edited by Sergio Bittanti
Edition
Softcover reprint of hardcover 1st ed. 1996
Illustrations
XXI, 552 p.
Pages
552
Dimensions
152x229x33
ISBN-13
9783642082481
Product ID
9985773

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