An identification algorithm for Hammerstein-Wiener system with dead zone input nonlinearity using gradient method
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: 2014DOI: 10.1109/APSIPA.2014.7041807
Keyword(s): Adaptive algorithms,Adaptive filters,Compressed sensing,Convergence,Least squares approximations,Steady-state,Vectors,Proportionate normalized least mean squares (PNLMS),compressed sensing,iterative hard thresholding (IHT),mean square deviation (MSD)
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An identification algorithm for Hammerstein-Wiener system with dead zone input nonlinearity using gradient method
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| contributor author | HyokChan Hong , Zhizhong Mao | |
| date accessioned | 2020-03-12T20:07:15Z | |
| date available | 2020-03-12T20:07:15Z | |
| date issued | 2014 | |
| identifier other | 6852596.pdf | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/1002625 | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | An identification algorithm for Hammerstein-Wiener system with dead zone input nonlinearity using gradient method | |
| type | Conference Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8123701 | |
| subject keywords | Adaptive algorithms | |
| subject keywords | Adaptive filters | |
| subject keywords | Compressed sensing | |
| subject keywords | Convergence | |
| subject keywords | Least squares approximations | |
| subject keywords | Steady-state | |
| subject keywords | Vectors | |
| subject keywords | Proportionate normalized least mean squares (PNLMS) | |
| subject keywords | compressed sensing | |
| subject keywords | iterative hard thresholding (IHT) | |
| subject keywords | mean square deviation (MSD) | |
| identifier doi | 10.1109/APSIPA.2014.7041807 | |
| journal title | ontrol and Decision Conference (2014 CCDC), The 26th Chinese | |
| filesize | 144918 | |
| citations | 0 |