Understand the benefits of robust statistics for signal processing with this authoritative yet accessible text. The first ever book on the subject, it provides a comprehensive overview of the field, moving from fundamental theory through to important new results and recent advances. Topics covered include advanced robust methods for complex-valued data, robust covariance estimation, penalized regression models, dependent data, robust bootstrap, and tensors. Robustness issues are illustrated throughout using real-world examples and key algorithms are included in a MATLAB Robust Signal Processing Toolbox accompanying the book online, allowing the methods discussed to be easily applied and adapted to multiple practical situations. This unique resource provides a powerful tool for researchers and practitioners working in the field of signal processing.

Understand the benefits of robust statistics for signal processing using this unique and authoritative text.

About the Author
Abdelhak M. Zoubir is a Professor of Signal Processing and the Head of the Signal Processing Group at Technische Universitat, Darmstadt, Germany. He is a Fellow of the IEEE, an IEEE Distinguished Lecturer, and the co-author of Bootstrap Techniques for Signal Processing (Cambridge, 2004). Visa Koivunen is a Professor of Signal Processing at Aalto University, Finland. He is also a Fellow of the IEEE and an IEEE Distinguished Lecturer. Esa Ollila is an Associate Professor of Signal Processing at Aalto University, Finland. Michael Muma is a Postdoctoral Research Fellow in the Signal Processing Group at Technische Universitat, Darmstadt, Germany.


Book Information
ISBN 9781107017412
Author Abdelhak M. Zoubir
Format Hardback
Page Count 312
Imprint Cambridge University Press
Publisher Cambridge University Press
Weight(grams) 770g
Dimensions(mm) 253mm * 178mm * 18mm