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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Vydané v:	IEEE transactions on circuits and systems. II, Express briefs Ročník 68; číslo 7; s. 2725 - 2729
Hlavní autori:	Jain, Sandesh, Mitra, Rangeet, Bhatia, Vimal
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.07.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
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