Robust Statistics for Signal Processing
doi.org/10.1017/9781139084291
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.
Co-authors
- Abdelhak M. Zoubir, Technische Universit�t, Darmstadt, Germany
- Visa Koivunen, Aalto University, Finland
- Michael Muma, Technische Universit�t, Darmstadt, Germany
Matlab Toolbox
A comprehensive MATLAB robust signal processing toolbox is accompanying the book. You can found it at github: https://github.com/RobustSP/toolbox