Sircar Mathematical Aspects of Signal Processing

Erscheinungsjahr 2017
ISBN: 978-1-316-81170-2
Verlag: Cambridge University Press
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 0 Seiten

Written using clear and accessible language, this text provides detailed coverage of the core mathematical concepts underpinning signal processing. All the core areas of mathematics are covered, including generalized inverses, singular value decomposition, function representation, and optimization, with detailed explanations of how basic concepts in these areas underpin the methods used to perform signal processing tasks. A particular emphasis is placed on the practical applications of signal processing, with numerous in-text practice questions and real-world examples illustrating key concepts, and MATLAB programs with accompanying graphical representations providing all the necessary computational background. This is an ideal text for graduate students taking courses in signal processing and mathematical methods, or those who want to establish a firm foundation in these areas before progressing to more advanced study.

Autoren/Hrsg.

Sircar, Pradip

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie

Inhaltsverzeichnis

Acknowledgements; Foreword; List of tables; List of figures; 1. Paradigm of signal processing; 2. Function representation; 3. Generalized inverse; 4. Modal decomposition; 5. Optimization; Solutions to problems; Index.

Über Autor(innen)

Sircar, Pradip
Pradip Sircar is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology, Kanpur. He is the co-author of Non-stationary Signal Analysis: Methods Based on Fourier-Bessel Representation (2010) and has published articles in many leading scientific journals.