The Nearest-Instance-Centroid-Estimation Kernel Recursive Least Squares Algorithms

The nearest-instance-centroid-estimation kernel least mean-square (NICE-KLMS) algorithm has been proposed to balance the time and space requirements in kernel adaptive filters. However, the minimum mean square error (MMSE) criterion used in NICE-KLMS leads to performance degradation in some nonlinea...

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Veröffentlicht in:	IEEE transactions on circuits and systems. II, Express briefs Jg. 67; H. 7; S. 1344 - 1348
Hauptverfasser:	Zhang, Haonan, Wang, Lin, Zhang, Tao, Wang, Shiyuan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.07.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptive filters Algorithms Centroids Circuits and systems Clustering algorithms Computer simulation Dictionaries Kernel kernel recursive least squares algorithm Kernels Least squares Mean square error methods minimum mean square error Nearest-instance-centroid-estimation nonlinear problems Performance degradation Prediction algorithms quantization Signal processing algorithms Vector quantization
ISSN:	1549-7747, 1558-3791
Online-Zugang:	Volltext
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