Time-frequency domain for segmentation and classification of non-stationary signals : the Stockwell Transform applied on bio-signals and electric signals /

"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,...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Moukadem, Ali (Συγγραφέας), Abdeslam, Djaffar Ould (Συγγραφέας), Dieterlen, Alain (Συγγραφέας)
Μορφή: Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: London : Hoboken, NJ : ISTE ; Wiley, 2014.
Σειρά:Focus nanoscience and nanotechnology series.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Moukadem, Ali,  |e author. 
245 1 0 |a Time-frequency domain for segmentation and classification of non-stationary signals :  |b the Stockwell Transform applied on bio-signals and electric signals /  |c Ali Moukadem, Djaffar Ould Abdeslam, Alain Dieterlen. 
264 1 |a London :  |b ISTE ;  |a Hoboken, NJ :  |b Wiley,  |c 2014. 
264 4 |c ©2014 
300 |a 1 online resource (xi, 135 pages) :  |b illustrations. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a FOCUS Series 
504 |a Includes bibliographical references and index. 
505 0 |a The Need for Time-Frequency Analysis / Ali Moukadem, Djaffar Ould Abdeslam, Alain Dieterlen -- Time-Frequency Analysis:The S-Transform / Ali Moukadem, Djaffar Ould Abdeslam, Alain Dieterlen -- Segmentation and Classification of Heart Sounds Based on the S-Transform / Ali Moukadem, Djaffar Ould Abdeslam, Alain Dieterlen -- Adaline for the Detection of Electrical Events in Electrical Signals / Ali Moukadem, Djaffar Ould Abdeslam, Alain Dieterlen -- FPGA Implementation of the Adaline / Ali Moukadem, Djaffar Ould Abdeslam, Alain Dieterlen. 
520 |a "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."--Provided by publisher. 
588 0 |a Online resource; title from PDF title page (Wiley, viewed May 5, 2014). 
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650 7 |a Software engineering.  |2 fast  |0 (OCoLC)fst01124185 
655 4 |a Electronic books. 
655 0 |a Electronic books. 
700 1 |a Abdeslam, Djaffar Ould,  |e author. 
700 1 |a Dieterlen, Alain,  |e author. 
776 0 8 |i Print version:  |a Moukadem, Ali.  |t Time-frequency domain for segmentation and classification of non-stationary signals.  |d London : ISTE Ltd ; Hoboken, NJ : John Wiley & Sons, Inc., 2014  |z 9781848216136  |w (DLC) 2014930208  |w (OCoLC)876882922 
830 0 |a Focus nanoscience and nanotechnology series. 
856 4 0 |u https://doi.org/10.1002/9781118908686  |z Full Text via HEAL-Link 
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