Improved-Variable-Forgetting-Factor Recursive Algorithm Based on the Logarithmic Cost for Volterra System Identification

Compared with the least-mean-square algorithm, the least mean pth power algorithm shows a better robustness performance against impulsive noises such as the α-stable noises. However, it still exhibits slow convergence rate and high kernel misadjustment. To overcome this drawback, a novel recursive l...

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Veröffentlicht in:	IEEE transactions on circuits and systems. II, Express briefs Jg. 63; H. 6; S. 588 - 592
Hauptverfasser:	Lu, Lu, Zhao, Haiquan, Chen, Badong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.06.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptive filters Adaptive recursive algorithm Algorithms Convergence Cost function Estimation Kernel Noise Nonlinear systems Performance enhancement Recursive Robustness Signal processing algorithms System identification Tracking Variable forgetting factor (VFF) Volterra system α-stable noise alpha-stable noise Volterra system adaptive recursive algorithm Adaptive filters variable forgetting factor (VFF)
ISSN:	1549-7747, 1558-3791
Online-Zugang:	Volltext
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