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LEADER 00000cam a2200217 a 4500 
008    190320s2019    xxka   f      001 0 eng d 
020    9780128174449 
040    AE-AjAUL|cAE-ShKH 
050 14 R857.B54|bS833 2019 
100 1  Subasi, Abdulhamit 
245 10 Practical guide for biomedical signals analysis using 
       machine learning techniques :|ba MATLAB based approach /
       |cAbdulhamit Subasi. 
260    London :|bAcademic Press, an imprint of Elsevier,|c2019. 
300    xi, 443 p. :|bill. ;|c29 cm. 
500    KH-AUL-3 
500    Includes index 
505 0  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.-- |c Source 
       other than Library of Congress. 
650  0 Artificial intelligence|xMedical applications 
650  0 Biosensors 
650  0 Signal processing|xDigital techniques