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Taschenbuch. Condition: Neu. Speech and Audio Processing for Coding, Enhancement and Recognition | Tokunbo Ogunfunmi (u. a.) | Taschenbuch | x | Englisch | 2016 | Humana | EAN 9781493948048 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Paperback. Condition: Brand New. 300 pages. 9.00x6.00x0.50 inches. In Stock.
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Hardcover. Condition: Brand New. 345 pages. 9.25x6.25x1.00 inches. In Stock.
Language: English
Published by Springer New York, Springer US, 2016
ISBN 10: 1493948040 ISBN 13: 9781493948048
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes the basic principles underlying the generation, coding, transmission and enhancement of speech and audio signals, including advanced statistical and machine learning techniques for speech and speaker recognition with an overview of the key innovations in these areas. Key research undertaken in speech coding, speech enhancement, speech recognition, emotion recognition and speaker diarization are also presented, along with recent advances and new paradigms in these areas.
Taschenbuch. Condition: Neu. Adaptive Nonlinear System Identification | The Volterra and Wiener Model Approaches | Tokunbo Ogunfunmi | Taschenbuch | Signals and Communication Technology | xvi | Englisch | 2010 | Springer | EAN 9781441938831 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches introduces engineers and researchers to the field of nonlinear adaptive system identification. The book includes recent research results in the area of adaptive nonlinear system identification and presents simple, concise, easy-to-understand methods for identifying nonlinear systems. These methods use adaptive filter algorithms that are well known for linear systems identification. They are applicable for nonlinear systems that can be efficiently modeled by polynomials. After a brief introduction to nonlinear systems and to adaptive system identification, the author presents the discrete Volterra model approach. This is followed by an explanation of the Wiener model approach. Adaptive algorithms using both models are developed. The performance of the two methods are then compared to determine which model performs better for system identification applications. Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches is useful to graduates students, engineers and researchers in the areas of nonlinear systems, control, biomedical systems and in adaptive signal processing.
Condition: As New. Unread book in perfect condition.