Digital Signal Processing Kernel by Rojo Alvarez Jose (14 results)

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Hardcover. Condition: new. Hardcover. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardback. Condition: New. New copy - Usually dispatched within 4 working days. 1258.

Condition: New.

Hardcover. Condition: new. Hardcover. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Buch. Condition: Neu. Neuware.

Hardcover. Condition: Brand New. 639 pages. 10.00x7.00x1.25 inches. In Stock.

Condition: New. Num Pages: 416 pages. BIC Classification: TJK; UT; UYS. Category: (P) Professional & Vocational. . . 2018. 1st Edition. Hardcover. . . . .

Hardcover. Condition: new. Hardcover. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condition: New. Num Pages: 416 pages. BIC Classification: TJK; UT; UYS. Category: (P) Professional & Vocational. . . 2018. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Hardcover. Condition: Brand New. 639 pages. 10.00x7.00x1.25 inches. In Stock. This item is printed on demand.

Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 1258.