Digital signal processing with kernel methods /

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Offering example applications and detailed benchmarking experiments with real and synthetic datasets throughout, this book provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. --

Bibliographic Details
Call Number:Libro Electrónico
Main Authors: Rojo-Álvarez, José Luis, 1972- (Author), Martínez-Ramón, Manel, 1968- (Author), Muñoz Marí, Jordi (Author), Camps-Valls, Gustavo, 1972- (Author)
Format: Electronic eBook
Language:Inglés
Published: Hoboken, NJ : Wiley, 2017.
Edition:First edition.
Subjects:
Signal processing > Digital techniques.
Traitement du signal > Techniques numériques.
TECHNOLOGY & ENGINEERING > Mechanical.
Signal processing > Digital techniques
Online Access:Texto completo (Requiere registro previo con correo institucional)
Table of Contents:
  • From signal processing to machine learning
  • Introduction to digital signal processing
  • Signal processing models
  • Kernel functions and reproducing kernel hilbert spaces
  • A SVM signal estimation framework
  • Reproducing kernel hilbert space models for signal processing
  • Dual signal models for signal processing
  • Advances in kernel regression and function approximation
  • Adaptive kernel learning for signal processing
  • SVM and kernel classification algorithms
  • Clustering and anomaly detection with kernels
  • Kernel feature extraction in signal processing.

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