Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals: The Stockwell Transform Applied on Bio-signals and Electric Signals
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 domai...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Somerset
Wiley
2014
|
| Ausgabe: | 1st ed |
| Schriftenreihe: | FOCUS
|
| Schlagworte: | |
| Zusammenfassung: | 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 |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 online resource (149 pages) |
| ISBN: | 9781118908778 9781118908686 |
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| 520 | |a 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 | ||
| 650 | 4 | |a Mathematik | |
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| id | DE-604.BV043608192 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:30:51Z |
| institution | BVB |
| isbn | 9781118908778 9781118908686 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029022251 |
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| spelling | Moukadem, Ali Verfasser aut Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals The Stockwell Transform Applied on Bio-signals and Electric Signals 1st ed Somerset Wiley 2014 © 2014 1 online resource (149 pages) txt rdacontent c rdamedia cr rdacarrier FOCUS Description based on publisher supplied metadata and other sources 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 Mathematik Signal processing -- Digital techniques Signal processing -- Mathematics Abdeslam, Djaffar Ould Sonstige oth Dieterlen, Alain Sonstige oth Erscheint auch als Druck-Ausgabe Moukadem, Ali Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals : The Stockwell Transform Applied on Bio-signals and Electric Signals |
| spellingShingle | Moukadem, Ali Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals The Stockwell Transform Applied on Bio-signals and Electric Signals Mathematik Signal processing -- Digital techniques Signal processing -- Mathematics |
| title | Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals The Stockwell Transform Applied on Bio-signals and Electric Signals |
| title_auth | Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals The Stockwell Transform Applied on Bio-signals and Electric Signals |
| title_exact_search | Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals The Stockwell Transform Applied on Bio-signals and Electric Signals |
| title_full | Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals The Stockwell Transform Applied on Bio-signals and Electric Signals |
| title_fullStr | Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals The Stockwell Transform Applied on Bio-signals and Electric Signals |
| title_full_unstemmed | Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals The Stockwell Transform Applied on Bio-signals and Electric Signals |
| title_short | Time-Frequency Domain for Segmentation and Classification of Non-stationary Signals |
| title_sort | time frequency domain for segmentation and classification of non stationary signals the stockwell transform applied on bio signals and electric signals |
| title_sub | The Stockwell Transform Applied on Bio-signals and Electric Signals |
| topic | Mathematik Signal processing -- Digital techniques Signal processing -- Mathematics |
| topic_facet | Mathematik Signal processing -- Digital techniques Signal processing -- Mathematics |
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