Modified Clipped LMS Algorithm
سال
: 2005
چکیده: A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is amodification of an existing
method, namely, the clipped LMS, and uses a three-level quantization (+1, 0,−1) scheme that involves the threshold clipping of
the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the
optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS) algorithm has better
tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified
one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS
algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.
method, namely, the clipped LMS, and uses a three-level quantization (+1, 0,−1) scheme that involves the threshold clipping of
the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the
optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS) algorithm has better
tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified
one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS
algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.
کلیدواژه(گان): adaptive filter,LMS algorithm,clipped LMS algorithm,modified clipped LMS algorithm
کالکشن
:
-
آمار بازدید
Modified Clipped LMS Algorithm
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| contributor author | هادی صدوقی یزدی | en |
| contributor author | Hadi Sadoghi Yazdi | fa |
| date accessioned | 2020-06-06T13:55:09Z | |
| date available | 2020-06-06T13:55:09Z | |
| date issued | 2005 | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/3374728 | |
| description abstract | A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is amodification of an existing method, namely, the clipped LMS, and uses a three-level quantization (+1, 0,−1) scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS) algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented. | en |
| language | English | |
| title | Modified Clipped LMS Algorithm | en |
| type | Journal Paper | |
| contenttype | External Fulltext | |
| subject keywords | adaptive filter | en |
| subject keywords | LMS algorithm | en |
| subject keywords | clipped LMS algorithm | en |
| subject keywords | modified clipped LMS algorithm | en |
| journal title | Eurasip Journal on Advanced Signal Processing | en |
| journal title | EURASIP Journal on Advanced Signal Processing | fa |
| pages | 10-Jan | |
| journal volume | 0 | |
| journal issue | 0 | |
| identifier link | https://profdoc.um.ac.ir/paper-abstract-1010153.html | |
| identifier articleid | 1010153 |