Kernael Least Mean Square Algorithm Based on Block Adaptive Filtering
Kernel Least Mean Square(KLMS) algorithm has a good covergence performance in nonlinear systems.But its mean square error gradient is estimated by the instantaneous gradient that results in larger randomness.However,the block adaptive filtering theory can reduce the steady-state error of KLMS algori...
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Editorial Office of Computer Engineering
2017-09-01
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| Schriftenreihe: | Jisuanji gongcheng |
| Schlagworte: | |
| Online-Zugang: | https://www.ecice06.com/fileup/1000-3428/PDF/201709029.pdf |
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