(Wiley - IEEE) 1st Edition
by Jose Luis Rojo-Alvarez (Author), Manel Martinez-Ramon (Author), Jordi Munoz-Mari (Author), Gustau Camps-Valls (Author)
A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems
Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research.
Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field.
• Presents the necessary basic ideas from both digital signal processing and machine learning concepts
• Reviews the state-of-the-art in SVM algorithms for classification and detection problems in the context of signal processing
•
Surveys advances in kernel signal processing beyond SVM algorithms to
present other highly relevant kernel methods for digital signal
processing
An excellent book for signal processing researchers and practitioners, Digital Signal Processing with Kernel Methods will also appeal to those involved in machine learning and pattern recognition.
