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Herausgeber: 
  • Amine Nait-Ali
  • Advanced Biosignal Processing 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Oktober 2010  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Applied mathematics / Artificial Intelligence / B / Biomathematics / Biomedical engineering / Biomedical Engineering and Bioengineering / Cardiology / Cardiovascular medicine / Complex systems / Computational Intelligence / Computer Imaging, Vision, Pattern Recognition and Graphics / Computer Vision / Dynamical systems / Dynamics & statics / engineering / INTERNAL MEDICINE / Mathematical and Computational Biology / Optical data processing / Physiological, Cellular and Medical Topics / Statistical physics
    ISBN:  9783642100451 
    EAN-Code: 
    9783642100451 
    Verlag:  Springer Berlin Heidelberg 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 25 mm 
    Gewicht:  671 gr 
    Seiten:  396 
    Zus. Info:  Paperback 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Through 17 chapters, this book presents the principle of many advanced biosignal processing techniques. After an important chapter introducing the main biosignal properties as well as the most recent acquisition techniques, it highlights five specific parts which build the body of this book. Each part concerns one of the most intensively used biosignals in the clinical routine, namely the Electrocardiogram (ECG), the Elektroenzephalogram (EEG), the Electromyogram (EMG) and the Evoked Potential (EP). In addition, each part gathers a certain number of chapters related to analysis, detection, classification, source separation and feature extraction. These aspects are explored by means of various advanced signal processing approaches, namely wavelets, Empirical Modal Decomposition, Neural networks, Markov models, Metaheuristics as well as hybrid approaches including wavelet networks, and neuro-fuzzy networks.

    The last part, concerns the Multimodal Biosignal processing, in which we present two different chapters related to the biomedical compression and the data fusion.

    Instead organising the chapters by approaches, the present book has been voluntarily structured according to signal categories (ECG, EEG, EMG, EP). This helps the reader, interested in a specific field, to assimilate easily the techniques dedicated to a given class of biosignals. Furthermore, most of signals used for illustration purpose in this book can be downloaded from the Medical Database for the Evaluation of Image and Signal Processing Algorithm. These materials assist considerably the user in evaluating the performances of their developed algorithms.

    This book is suited for final year graduate students, engineers and researchers in biomedical engineering and practicing engineers in biomedical science and medical physics.

      
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