The independent component analysis (ICA) problem originates from many practical areas, but there has not been any mathematical theory to solve it completely. In this paper, we establish a mathematical theory to solve it under the condition that the number of super-Gaussian sources is known. According to this theory, a step by step optimization algorithm is proposed and demonstrated well on solving the ICA problem with both the super- and sub-Gaussian sources. ? Springer-Verlag Berlin Heidelberg 2005.EI
Independent Components Analysis (ICA) is a blind source separation method that has been developed to...
International audienceThe independent component analysis (ICA) of a random vector consists of search...
Independent component analysis (ICA) – the theory of mixed, independent, non-Gaussian sources – has ...
The Independent Component Analysis (ICA) of a random vector consists of searching for the linear tra...
Independent component analysis (ICA) has been applied in many fields of signal processing and many I...
Abstract. This paper derives a new algorithm that performs independent component analysis (ICA) by o...
International audienceWe study optimization methods for solving the maximum likelihood formulation o...
A new fixed-point algorithm for independent component analysis (ICA) is presented that is able blind...
ABSTRACT: The independent component analysis of a random vector consists of finding for a linear tra...
Many algorithms based on information theoretic measures and/or temporal statistics of the signals ha...
The one-bit-matching conjecture for independent component analysis (ICA) has been widely believed in...
This article develops an extended independent component analysis algorithm for mixtures of arbitrary...
In solving the problem of noiseless independent component analysis (ICA) in which sources of super- ...
We present a new algorithm for Independent Component Analysis (ICA) which has provable performance g...
Abstract. This paper addresses an independent component analysis (ICA) learning algorithm with exibl...
Independent Components Analysis (ICA) is a blind source separation method that has been developed to...
International audienceThe independent component analysis (ICA) of a random vector consists of search...
Independent component analysis (ICA) – the theory of mixed, independent, non-Gaussian sources – has ...
The Independent Component Analysis (ICA) of a random vector consists of searching for the linear tra...
Independent component analysis (ICA) has been applied in many fields of signal processing and many I...
Abstract. This paper derives a new algorithm that performs independent component analysis (ICA) by o...
International audienceWe study optimization methods for solving the maximum likelihood formulation o...
A new fixed-point algorithm for independent component analysis (ICA) is presented that is able blind...
ABSTRACT: The independent component analysis of a random vector consists of finding for a linear tra...
Many algorithms based on information theoretic measures and/or temporal statistics of the signals ha...
The one-bit-matching conjecture for independent component analysis (ICA) has been widely believed in...
This article develops an extended independent component analysis algorithm for mixtures of arbitrary...
In solving the problem of noiseless independent component analysis (ICA) in which sources of super- ...
We present a new algorithm for Independent Component Analysis (ICA) which has provable performance g...
Abstract. This paper addresses an independent component analysis (ICA) learning algorithm with exibl...
Independent Components Analysis (ICA) is a blind source separation method that has been developed to...
International audienceThe independent component analysis (ICA) of a random vector consists of search...
Independent component analysis (ICA) – the theory of mixed, independent, non-Gaussian sources – has ...