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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Bibliographic Details
Published in:	IEEE transactions on circuits and systems. II, Express briefs Vol. 67; no. 7; pp. 1344 - 1348
Main Authors:	Zhang, Haonan, Wang, Lin, Zhang, Tao, Wang, Shiyuan
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.07.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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 Access:	Get full text
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