Kernel Recursive Maximum Versoria Criterion Algorithm Using Random Fourier Features

Reproducing Hilbert space (RKHS)-based adaptive algorithms have attracted increased attention in machine learning and nonlinear signal processing with applications in visible light communications, radar, radio frequency communications and others. However, performance of RKHS-based algorithms is high...

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Bibliographic Details
Published in:	IEEE transactions on circuits and systems. II, Express briefs Vol. 68; no. 7; pp. 2725 - 2729
Main Authors:	Jain, Sandesh, Mitra, Rangeet, Bhatia, Vimal
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.07.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptive algorithms Adaptive filters Algorithms Computational complexity Convergence correntropy Criteria Hilbert space Kernel Kernels Machine learning minimum mean square error Prediction algorithms RFF RKHS Signal processing Signal processing algorithms Steady-state Versoria criterion Visible light communication
ISSN:	1549-7747, 1558-3791
Online Access:	Get full text
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