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Record Nr. |
UNINA9910810934503321 |
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Autore |
Rojo-Álvarez José Luis <1972-> |
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Titolo |
Digital signal processing with kernel methods / / by Dr. José Luis Rojo-Álvarez, Dr. Manel Martínez-Ramón, Dr. Jordi Muñoz-Marí, Dr. Gustau Camps-Valls |
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Pubbl/distr/stampa |
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Hoboken, New Jersey : , : Wiley, , 2018 |
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[Piscataqay, New Jersey] : , : IEEE Xplore, , [2018] |
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ISBN |
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1-118-70583-1 |
1-118-70582-3 |
1-118-70581-5 |
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Edizione |
[First edition.] |
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Descrizione fisica |
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1 online resource (668 pages) : illustrations |
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Disciplina |
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Soggetti |
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Signal processing - Digital techniques |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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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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Sommario/riassunto |
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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 |
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