543 search results - page 32 / 109 » Nonlinear principal component analysis of noisy data |
ICPR
2008
IEEE
14 years 9 months ago
2008
IEEE
Speaker independent feature extraction is a critical problem in speech recognition. Oriented principal component analysis (OPCA) is a potential solution that can find a subspace r...
SCIA
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. Moving objects detection is a crucial step for video surveillance systems. The segmentation performed by motion detection algorithms is often noisy, which makes it hard t...
ICA
2004
Springer
2004
Springer
Using Kernel PCA for Initialisation of Variational Bayesian Nonlinear Blind Source Separation Method
14 years 1 months ago
The variational Bayesian nonlinear blind source separation method introduced by Lappalainen and Honkela in 2000 is initialised with linear principal component analysis (PCA). Becau...
ROMAN
2007
IEEE
14 years 1 months ago
2007
IEEE
— In this work, we perform an extensive statistical evaluation for learning and recognition of object manipulation actions. We concentrate on single arm/hand actions but study th...
SDM
2011
SIAM
12 years 10 months ago
2011
SIAM
Sparse principal component analysis (PCA) imposes extra constraints or penalty terms to the standard PCA to achieve sparsity. In this paper, we first introduce an efficient algor...