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ICCV
2011
IEEE
13 years 9 months ago
Localized Principal Component Analysis based Curve Evolution: A Divide and Conquer Approach
We propose a novel localized principal component analysis (PCA) based curve evolution approach which evolves the segmenting curve semi-locally within various target regions (divis...
Vikram Appia, Balaji Ganapathy, Tracy Faber, Antho...
76
Voted
IJCNN
2000
IEEE
15 years 2 months ago
ICA for Noisy Neurobiological Data
ICA (Independent Component Analysis) is a new technique for analyzing multi-variant data. Lots of results are reported in the field of neurobiological data analysis such as EEG (...
Shiro Ikeda, Keisuke Toyama
AMCS
2008
146views Mathematics» more  AMCS 2008»
14 years 9 months ago
Fault Detection and Isolation with Robust Principal Component Analysis
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance...
Yvon Tharrault, Gilles Mourot, José Ragot, ...
93
Voted
COLT
2004
Springer
15 years 3 months ago
Statistical Properties of Kernel Principal Component Analysis
The main goal of this paper is to prove inequalities on the reconstruction error for Kernel Principal Component Analysis. With respect to previous work on this topic, our contribu...
Laurent Zwald, Olivier Bousquet, Gilles Blanchard
78
Voted
TSP
2008
174views more  TSP 2008»
14 years 9 months ago
Complex ICA Using Nonlinear Functions
We introduce a framework based on Wirtinger calculus for nonlinear complex-valued signal processing such that all computations can be directly carried out in the complex domain. Th...
Tülay Adali, Hualiang Li, Mike Novey, J.-F. C...