Digital Signal Processing with Kernel Methods
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…
Read More ↓Title Statements
- Full title :Digital Signal Processing with Kernel Methods / José Luis Rojo-Álvarez, Manel Martínez-Ramón, Jordi Muñoz-Marí, Gustau Camps-Valls
Summary
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.
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.
Edition Statements
- Publication Date:2017
- Edition:1. Auflage
Publication Statements
- Publisher(s):John Wiley & Sons
- Place of Publication:New York
- Language:eng
- Publication Date:2017
Notes
Lizenzpflichtig
The Physical Object
- Description:Online-Ressource, 672 Seiten.
Edition Identifiers
- ISBN:9781118705827, 1118705823, 1118705831, 1118705815, 9781118705810, 9781118705834
- DOI:10.1002/9781118705810
- oclc:on1148180265
- LC Classification:TK5102.9
- Dewey Decimal:621.3
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