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04171nam a2200745 4500 |
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ocn874321835 |
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OCoLC |
| 005 |
20170124070734.2 |
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m o d |
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cr cnu|||unuuu |
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140322t20142014enka ob 001 0 eng d |
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|a EBLCP
|b eng
|e rda
|e pn
|c EBLCP
|d IDEBK
|d DG1
|d OCLCQ
|d E7B
|d CUS
|d YDXCP
|d CDX
|d N$T
|d OCLCO
|d DEBSZ
|d RECBK
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| 019 |
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|a 876346418
|a 880340229
|a 961553265
|a 962561498
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|a 9781118908686
|q (electronic bk.)
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|q (electronic bk.)
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|q (electronic bk.)
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|z 9781848216136
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| 035 |
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|a (OCoLC)874321835
|z (OCoLC)876346418
|z (OCoLC)880340229
|z (OCoLC)961553265
|z (OCoLC)962561498
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| 037 |
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|a 584586
|b MIL
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| 050 |
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4 |
|a QA76.758
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| 072 |
|
7 |
|a COM
|x 051000
|2 bisacsh
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| 072 |
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|a COM
|x 051230
|2 bisacsh
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| 082 |
0 |
4 |
|a 005.1
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| 049 |
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|a MAIN
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| 100 |
1 |
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|a Moukadem, Ali,
|e author.
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| 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.
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| 264 |
|
1 |
|a London :
|b ISTE ;
|a Hoboken, NJ :
|b Wiley,
|c 2014.
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| 264 |
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4 |
|c ©2014
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| 300 |
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|a 1 online resource (xi, 135 pages) :
|b illustrations.
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| 336 |
|
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 490 |
1 |
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|a FOCUS Series
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| 504 |
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|a Includes bibliographical references and index.
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| 505 |
0 |
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|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 |
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|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.
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| 588 |
0 |
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|a Online resource; title from PDF title page (Wiley, viewed May 5, 2014).
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| 650 |
|
0 |
|a Signal processing
|x Digital techniques
|x Data processing.
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| 650 |
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0 |
|a Software engineering.
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| 650 |
|
4 |
|a Information technology.
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| 650 |
|
4 |
|a Software engineering.
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| 650 |
|
7 |
|a COMPUTERS
|x Programming
|x General.
|2 bisacsh
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| 650 |
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7 |
|a COMPUTERS
|x Programming
|x Software Development.
|2 bisacsh
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| 650 |
|
7 |
|a Signal processing
|x Digital techniques
|x Data processing.
|2 fast
|0 (OCoLC)fst01118288
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| 650 |
|
7 |
|a Software engineering.
|2 fast
|0 (OCoLC)fst01124185
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| 655 |
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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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| 994 |
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|a 92
|b DG1
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