Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques - A MATLAB Based Approach (Paperback)

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.

General

Imprint:	Academic Press Inc
Country of origin:	United States
Release date:	March 2019
First published:	2019
Authors:	Abdulhamit Subasi
Dimensions:	235 x 191mm (L x W)
Format:	Paperback
Pages:	456
ISBN-13:	978-0-12-817444-9
Categories:	Books > Medicine > Nursing & ancillary services > Biomedical engineering > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Promotions
LSN:	0-12-817444-7
Barcode:	9780128174449

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