Adaptive Multiregression in Reproducing Kernel Hilbert Spaces: The Multiaccess MIMO Channel Case

This paper introduces a wide framework for online, i.e., time-adaptive, supervised multiregression tasks. The problem is formulated in a general infinite-dimensional reproducing kernel Hilbert space (RKHS). In this context, a fairly large number of nonlinear multiregression models fall as special ca...

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Vydané v:	IEEE transaction on neural networks and learning systems Ročník 23; číslo 2; s. 260 - 276
Hlavní autori:	Slavakis, K., Bouboulis, P., Theodoridis, S.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.02.2012 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptive kernel learning Algorithms Channels convex analysis Convex functions Hilbert space Kernel Kernels Loss measurement Mathematical analysis Mathematical models MIMO multiple-input multiple-output channel equalization On-line systems Online projection regression Signal processing Studies subgradient Tasks Training data
ISSN:	2162-237X, 2162-2388
On-line prístup:	Získať plný text
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