Classification, Parameter Estimation and State Estimation

An Engineering Approach Using MatLab

Ferdinand van der Heijden, Robert Duin, Dick de Ridder, David M. J. Tax

424 pages, parution le 08/10/2004

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Résumé

Classification, Parameter Estimation and State Estimation is a practical and concise inter-disciplinary guide for data analysts and designers interested in advanced measurement-based systems. Highlighting the practical deployment of theoretical issues, the book provides a useful experimentation platform for skilled engineers to implement and evaluate design concepts.

Features:

A fully integrated and unified approach to parameter estimation, pattern classification and optimal (state) estimation.
An introduction to emerging techniques such as support vector machines and particle filtering.
Implementations in Matlab using the PRTools toolbox, with appendices providing the necessary documentation and useful functions for this and other existing toolboxes.
End-of-chapter exercises and numerous worked out examples within the text and on the Internet.

A valuable text for students and researchers in engineering, computer science, physics and applied mathematics, this book will also prove an essential reference for the practising civil, control, electrical and mechanical engineer.

Sommaire

Detection and Classification
Parameter estimation
State estimation
Supervised learning
Feature extraction and selection
Unsupervised learning
State estimation in practice
Worked out examples

Appendix A Topics selected from functional analysis
Appendix B Topics selected from linear algebra and matrix theory
Appendix C Probability theory
Appendix D Discrete-time dynamic systems
Appendix E Introduction to PRTools
Appendix F Used MATLAB toolboxes

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Ferdinand van der Heijden, Robert Duin, Dick de Ridder, David M. J. Tax
Parution	08/10/2004
Nb. de pages	424
Format	15,5 x 23,5
Couverture	Relié
Poids	745g
Intérieur	Noir et Blanc
EAN13	9780470090138