NDLI: A novel augmented complex valued kernel LMS

Content Provider	IEEE Xplore Digital Library
Author	Tobar, F.A. Kuh, A. Mandic, D.P.
Copyright Year	2012
Description	Author affiliation: Department of Electrical Engineering, University of Hawaii, USA (Kuh, A.) \|\| Department of Electrical and Electronic Engineering, Imperial College London, UK (Tobar, F.A.; Mandic, D.P.)
Abstract	A novel class of complex valued kernel least mean square (CKLMS) algorithms is introduced with the aim to provide physical meaning to the mapping between the primal and dual space termed the independent CKLMS (iCKLMS). The general class of CKLMS algorithms is also extended in the widely linear sense to develop online kernel algorithms suitable for the processing of general complex valued signals, both circular and noncircular. The so-introduced augmented complex kernel least mean square (ACKLMS) algorithms are verified on adaptive prediction of nonlinear and nonstationary complex wind signals.
Starting Page	473
Ending Page	476
File Size	260171
Page Count	4
File Format	PDF
ISBN	9781467310703
ISSN	2151870X
e-ISBN	9781467310710
DOI	10.1109/SAM.2012.6250542
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Heuristic algorithms Least squares approximation Prediction algorithms Signal processing algorithms Wind forecasting Wind speed augmented complex LMS Complex augmented kernels kernel prediction noncircularity least mean square wind prediction widely linear modelling
Content Type	Text
Resource Type	Article

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