Isbn: 9780128174449 - Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: a Matlab Based Approach (8 results)

- Softcover
Seller: Amazing Books Pittsburgh, Pittsburgh, PA, U.S.A.Amazing Books Pittsburgh
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paperback. Condition: Good. Copyright 2019, no other dates provided, edition and printing unstated. Unmarked text, pages clean, binding still tight. Book is slightly curved from storage. Moderate surface wear on covers, creases along edges, bottom right portion of first 60 pages or so creased/bumped. A few nicks and smudges along outside edge of pages. Paperback. (1h).…

- Softcover
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- Softcover
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- Softcover
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- Softcover
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- Softcover
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- Softcover
Seller: moluna, Greven, Germanymoluna
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Condition: New. Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction Explains how to apply machine learning techniques to .

- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. Neuware - Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis.…