Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals: The Stockwell Transform Applied on Bio-signals and Electric Signals
Ali Moukadem · Djaffar Ould Abdeslam · Alain Dieterlen
Mar 2014 · John Wiley & Sons
Ebook
148
Pages
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About this ebook
This book focuses on signal processing algorithms based on the timefrequency domain. Original methods and algorithms are presented which are able to extract information from non-stationary signals such as heart sounds and power electric signals. The methods proposed focus on the time-frequency domain, and most notably the Stockwell Transform for the feature extraction process and to identify signatures. For the classification method, the Adaline Neural Network is used and compared with other common classifiers. Theory enhancement, original applications and concrete implementation on FPGA for real-time processing are also covered in this book.
About the author
Ali Moukadem is a post-doctoral researcher at the MIPS laboratory at the University of Haute Alsace in France. His research interests include time-frequency analysis, multi-resolution analysis, non-stationary signals, and biomedical signals.
Djaffar Ould Abdeslam is Associate-Professor at the University of Haute Alsace in France. His research interests include advanced and intelligent methods for power quality improvement and monitoring, the control of Active Power Filters (APF) with ANNs and fuzzy logic and the hardware implementation of ANNs.
Alain Dieterlen is Professor at the MIPS laboratory at the University of Haute Alsace in France. His research interests include instrumentation, image and signal processing.
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