Access the full text.
Sign up today, get DeepDyve free for 14 days.
L Hoegaerts, L De Lathauwer, I Goethals, J Suykens, J Vendewalle, B De Moor (2007)
Efficiently updating and tracking the dominant kernel principal componentsNeural Netw, 20
R Rosipal, LJ Trecho (2001)
Partial Least Squares in Reproducing Kernel Hilbert SpacesJ Mach Learn Res, 2
VN Ghate, SV Dudul (2009)
Fast induction machine fault detection using support vector machine based classifierWSEAS Trans Syst, 8
C Richard, JCM Bermudez, P Honeine (2009)
Online prediction of time series data with kernelsIEEE Trans Signal Process, 57
V Vovk (2008)
Leading trategies in competitive on-line predictionTheor Comput Sci, 405
VN Vapnik (1995)
The nature of statistical learning theory
S Gunter, NN Schraudolph, SVN Vishwanathan (2007)
Fast Iterative kernel principal component analysisJ Mach Learn Res, 8
W Wanga, C Mena, W Lub (2008)
Online prediction model based on support vector machineNeurocomputing, 71
VN Vapnik (1998)
Statistical learning theory
B Scholkopf, A Smola, KR Muller (1998)
Nonlinear component analysis as kernel eigenvalue problemNeural Comput, 10
N Cristianini, J Shawe-Taylor (2000)
An introduction to support vector machines
B Scholkopf, A Smola (2002)
Learning with kernels
This paper proposes the design and a comparative study of two proposed online kernel methods identification in the reproducing kernel Hilbert space and other two kernel method existing in the literature. The two proposed methods, titled SVD-KPCA, online RKPCA. The two other techniques named Sliding Window Kernel Recursive Least Square and the Kernel Recursive Least Square. The considered performances are the Normalized Means Square Error, the consumed time and the numerical complexity. All methods are evaluated by handling a chemical process known as the Continuous Stirred Tank Reactor and Wiener-Hammerstein benchmark.
Artificial Intelligence Review – Springer Journals
Published: May 3, 2011
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.