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» Bayesian source separation: beyond PCA and ICA
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ESANN
2006
13 years 5 months ago
Bayesian source separation: beyond PCA and ICA
Blind source separation (BSS) has become one of the major signal and image processing area in many applications. Principal component analysis (PCA) and Independent component analys...
Ali Mohammad-Djafari
ICA
2004
Springer
13 years 9 months ago
Using Kernel PCA for Initialisation of Variational Bayesian Nonlinear Blind Source Separation Method
The variational Bayesian nonlinear blind source separation method introduced by Lappalainen and Honkela in 2000 is initialised with linear principal component analysis (PCA). Becau...
Antti Honkela, Stefan Harmeling, Leo Lundqvist, Ha...
ICIP
2006
IEEE
14 years 5 months ago
Joint Dimensionality Reduction, Classification and Segmentation of Hyperspectral Images
Dimensionality reduction, spectral classification and segmentation are the three main problems in hyperspectral image analysis. In this paper we propose a Bayesian estimation appr...
Nadia Bali, Ali Mohammad-Djafari, Adel Mohammadpou...
ESANN
2006
13 years 5 months ago
Hierarchical markovian models for joint classification, segmentation and data reduction of hyperspectral images
Spectral classification, segmentation and data reduction are the three main problems in hyperspectral image analysis. In this paper we propose a Bayesian estimation approach which ...
Nadia Bali, Ali Mohammad-Djafari, Adel Mohammadpou...
ESANN
2006
13 years 5 months ago
Semi-Blind Approaches for Source Separation and Independent component Analysis
Abstract. This paper is a survey of semi-blind source separation approaches. Since Gaussian iid signals are not separable, simplest priors suggest to assume non Gaussian iid signal...
Massoud Babaie-Zadeh, Christian Jutten