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Nonlinear estimation and classification / David D. Denison ; Mark H. Hansen ; Christopher C. Holmes ; B. Mallick

Public ISBD Titre : Nonlinear estimation and classification Type de document : texte imprimé Auteurs : David D. Denison, Auteur ; Mark H. Hansen, Auteur ; Christopher C. Holmes, Auteur ; B. Mallick, Auteur Editeur : Berlin : Springer Année de publication : 2003 Collection : Lecture notes in statistics num. 171 Importance : VII-474 p. Présentation : ill. Format : 24 cm ISBN/ISSN/EAN : 978-0-387-95471-4 Note générale : Bibliogr.-Index Langues : Français (fre) Mots-clés : Estimation  theory Nonlinear  theories Estimation,  Théorie  de  l' Théories  non  linéaires Index. décimale : 519.22 Théorie statistique. Modèles statistiques. Statistiques mathématiques Résumé : Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data. This is due in part to recent advances in data collection and computing technologies. As a result, fundamental statistical research is being undertaken in a variety of different fields. Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing. The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics. The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future. Note de contenu : Contents -Longer Papers *Wavelet Statistical Models and Besov Spaces *Coarse-to-Fine Classification and Scene Labeling *Environmental Monitoring Using a Time Series of Satellite Images and Other Spatial Data Sets ... -Shorter Papers *Adaptive Sparse Regression *Multiscale Statistical Models *Wavelet Thresholding on Non-Equispaced Data ... Nonlinear estimation and classification [texte imprimé] / David D. Denison, Auteur ; Mark H. Hansen, Auteur ; Christopher C. Holmes, Auteur ; B. Mallick, Auteur . - Springer, 2003 . - VII-474 p. : ill. ; 24 cm. - (Lecture notes in statistics; 171) . ISBN : 978-0-387-95471-4 Bibliogr.-Index Langues : Français (fre) Mots-clés : Estimation  theory Nonlinear  theories Estimation,  Théorie  de  l' Théories  non  linéaires Index. décimale : 519.22 Théorie statistique. Modèles statistiques. Statistiques mathématiques Résumé : Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data. This is due in part to recent advances in data collection and computing technologies. As a result, fundamental statistical research is being undertaken in a variety of different fields. Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing. The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics. The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future. Note de contenu : Contents -Longer Papers *Wavelet Statistical Models and Besov Spaces *Coarse-to-Fine Classification and Scene Labeling *Environmental Monitoring Using a Time Series of Satellite Images and Other Spatial Data Sets ... -Shorter Papers *Adaptive Sparse Regression *Multiscale Statistical Models *Wavelet Thresholding on Non-Equispaced Data ...

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Code-barres	Cote	Support	Localisation	Section	Disponibilité	Etat_Exemplaire
047736	519.22 NON	Papier	Bibliothèque Centrale	Mathématiques	Disponible