Identification, Adaptation, Learning: The Science of Learning Models from Data: 153 (NATO ASI Subseries F:) - Tapa blanda

 
9783642082481: Identification, Adaptation, Learning: The Science of Learning Models from Data: 153 (NATO ASI Subseries F:)
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ISBN 10: 3642082483 ISBN 13: 9783642082481
Editorial: Springer, 2010

Sinopsis

This book offers a tutorial view of the science of learning models from data. It covers the most important approaches to linear modelling, nonlinear model construction from data, fuzzy logic based modelling, and optimization methods.

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Reseña del editor

This book collects the lectures given at the NATO Advanced Study Institute From Identijication to Learning held in Villa Olmo, Como, Italy, from August 22 to September 2, 1994. The school was devoted to the themes of Identijication, Adaptation and Learning, as they are currently understood in the Information and Contral engineering community, their development in the last few decades, their inter­ connections and their applications. These titles describe challenging, exciting and rapidly growing research areas which are of interest both to contral and communication engineers and to statisticians and computer scientists. In accordance with the general goals of the Institute, and notwithstanding the rat her advanced level of the topics discussed, the presentations have been generally kept at a fairly tutorial level. For this reason this book should be valuable to a variety of rearchers and to graduate students interested in the general area of Control, Signals and Information Pracessing. As the goal of the school was to explore a common methodologicalline of reading the issues, the flavor is quite interdisciplinary. We regard this as an original and valuable feature of this book.

Reseña del editor

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.

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Editorial
Springer
Año de publicación
2010
Idioma
Inglés
ISBN 10 
3642082483
ISBN 13 
9783642082481
Encuadernación
Tapa blanda
Número de páginas
584
Editor
Bittanti Sergio, Picci Giorgio
Contacto del fabricante
ProductSafety@springernature.com
ProductSafety@springernature.com

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