Robust Statistics for Signal Processing

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.

• The first ever book on robust signal processing
• Covers important new results and recent developments in robust signal processing
• Includes real-world examples from the authors' experience, demonstrating the relevance of the methods discussed
• Includes the key algorithms in a MATLAB Robust Signal Processing Toolbox, allowing methods to be easily applied