Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals

The Stockwell Transform Applied on Bio-signals and Electric Signals

Nonfiction, Science & Nature, Technology, Imaging Systems
Cover of the book Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals by Ali Moukadem, Djaffar Ould Abdeslam, Alain Dieterlen, Wiley
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Author: Ali Moukadem, Djaffar Ould Abdeslam, Alain Dieterlen ISBN: 9781118908709
Publisher: Wiley Publication: March 6, 2014
Imprint: Wiley-ISTE Language: English
Author: Ali Moukadem, Djaffar Ould Abdeslam, Alain Dieterlen
ISBN: 9781118908709
Publisher: Wiley
Publication: March 6, 2014
Imprint: Wiley-ISTE
Language: English

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.

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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.

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