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Abdeslam D.O., Dieterlen A., Moukadem A. Time-frequency domain for segmentation and classification of non-stationary signals: the Stockwell Transform applied on bio-signals and electric signals

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Abdeslam D.O., Dieterlen A., Moukadem A. Time-frequency domain for segmentation and classification of non-stationary signals: the Stockwell Transform applied on bio-signals and electric signals
Hoboken: Wiley-ISTE, 2014. - 135p.
Focuses on signal processing algorithms based on the time frequency 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.
The Need for Time-Frequency Analysis
Time-Frequency Analysis:The S-Transform
Segmentation and Classification of Heart Sounds Based on the S-Transform
Adaline for the Detection of Electrical Events in Electrical Signals
FPGA Implementation of the Adaline
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