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In den WarenkorbZustand: New. In.
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EUR 113,71
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
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In den WarenkorbHardcover. Zustand: Brand New. 224 pages. 9.25x6.25x0.75 inches. In Stock.
Sprache: Englisch
Verlag: Springer International Publishing, 2018
ISBN 10: 3319851977 ISBN 13: 9783319851976
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Robust Digital Processing of Speech Signals | Branko Kovacevic (u. a.) | Taschenbuch | xii | Englisch | 2018 | Springer International Publishing | EAN 9783319851976 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer International Publishing, Springer International Publishing, 2018
ISBN 10: 3319851977 ISBN 13: 9783319851976
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on speech signal phenomena, presenting a robustification of the usual speech generation models with regard to the presumed types of excitation signals, which is equivalent to the introduction of a class of nonlinear models and the corresponding criterion functions for parameter estimation. Compared to the general class of nonlinear models, such as various neural networks, these models possess good properties of controlled complexity, the option of working in 'online' mode, as well as a low information volume for efficient speech encoding and transmission. Providing comprehensive insights, the book is based on the authors' research, which has already been published, supplemented by additional texts discussing general considerations of speech modeling, linear predictive analysis and robust parameter estimation.
Sprache: Englisch
Verlag: Springer International Publishing, 2017
ISBN 10: 3319536117 ISBN 13: 9783319536118
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on speech signal phenomena, presenting a robustification of the usual speech generation models with regard to the presumed types of excitation signals, which is equivalent to the introduction of a class of nonlinear models and the corresponding criterion functions for parameter estimation. Compared to the general class of nonlinear models, such as various neural networks, these models possess good properties of controlled complexity, the option of working in 'online' mode, as well as a low information volume for efficient speech encoding and transmission. Providing comprehensive insights, the book is based on the authors' research, which has already been published, supplemented by additional texts discussing general considerations of speech modeling, linear predictive analysis and robust parameter estimation.