A novel augmented complex valued kernel LMS

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...

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Bibliographic Details
Published in2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM) pp. 473 - 476
Main Authors Tobar, F. A., Kuh, A., Mandic, D. P.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2012
Subjects
augmented complex LMS
Complex augmented kernels
Heuristic algorithms
Kernel
kernel prediction
least mean square
Least squares approximation
noncircularity
Prediction algorithms
Signal processing algorithms
widely linear modelling
Wind forecasting
wind prediction
Wind speed
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ISBN1467310700
9781467310703
ISSN1551-2282
DOI10.1109/SAM.2012.6250542

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Summary: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.
ISBN:1467310700
9781467310703
ISSN:1551-2282
DOI:10.1109/SAM.2012.6250542