Digital signal processing with kernel methods / by Dr. José Luis Rojo-Álvarez, Dr. Manel Martínez-Ramón, Dr. Jordi Muñoz-Marí, Dr. Gustau Camps-Valls.

Format:

Book

Author/Creator:

Rojo-Álvarez, José Luis, 1972- author.

Martínez-Ramón, Manel, 1968- author.

Muñoz Marí, Jordi, author.

Camps-Valls, Gustavo, 1972- author.

Language:

English

Subjects (All):

Signal processing--Digital techniques.

Signal processing.

Physical Description:

1 online resource (668 pages) : illustrations

Edition:

First edition.

Distribution:

[Piscataqay, New Jersey] : IEEE Xplore, [2018]

Place of Publication:

Hoboken, New Jersey : Wiley, 2018.

System Details:

text file

Summary:

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. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors. . 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.

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.

Notes:

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9781118705834

1118705831

9781118705827

1118705823

9781118705810

1118705815

OCLC:

1004376608