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Item #:
125834284
Digital Signal Processing with Kernel Methods (IEEE Press)
Item #:
125834284
USD 158
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Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field.
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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 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: http://github.com/DSPKM • 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.
| Item Weight | 3 lbs (1.36 kg) |
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Digital Signal Processing with Kernel Methods (IEEE Press)
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USD 158
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Features & Benefits
- Comprehensive review of machine learning and signal processing methods.
- Focus on practical applications in telecommunications, multimedia, and biomedical engineering.
- Covers fundamental concepts for easy understanding and application.
- Includes example applications and detailed benchmarking experiments.
- Access to additional Matlab source code for further exploration.
- Ideal for researchers and practitioners in signal processing and machine learning.
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