
Robust Statistics for Signal Processing
Cambridge University Press
Published on 8. November 2018
Book
Hardback
312 pages
978-1-107-01741-2 (ISBN)
Description
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.
More details
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Dimensions
Height: 250 mm
Width: 175 mm
Thickness: 21 mm
Weight
724 gr
ISBN-13
978-1-107-01741-2 (9781107017412)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Abdelhak M. Zoubir
Robust Statistics for Signal Processing
E-Book
11/2018
Cambridge University Press
€103.99
Available for download

Abdelhak M. Zoubir | Visa Koivunen | Esa Ollila
Robust Statistics for Signal Processing
E-Book
10/2018
Cambridge University Press
€124.99
Available for download
Persons
Abdelhak M. Zoubir is a Professor of Signal Processing and the Head of the Signal Processing Group at Technische Universitaet, 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 Universitaet, Darmstadt, Germany.
Author
Technische Universitaet, Darmstadt, Germany
Aalto University, Finland
Aalto University, Finland
Technische Universitaet, Darmstadt, Germany
Content
1. Introduction and foundations; 2. Robust estimation: the linear regression model; 3. Robust penalized regression in the linear model; 4. Robust estimation of location and scatter (covariance) matrix; 5. Robustness in sensor array processing; 6. Tensor models and robust statistics; 7. Robust filtering; 8. Robust methods for dependent data; 9. Robust spectral estimation; 10. Robust bootstrap methods; 11. Real-life applications.