This paper studies the problem of blind source separation (BSS) from instantaneous mixtures with the assumption that the source signals are mutually correlated.We propose a novel approach to BSS by using precoders in transmitters.We show that if the precoders are properly designed, some cross-correlation coefficients of the coded signals can be forced to be zero at certain time lags. Then, the unique correlation properties of the coded signals can be exploited in receiver to achieve source separation. Based on the proposed precoders, a subspace-based algorithm is derived for the blind separation of mutually correlated sources. The effectiveness of the algorithm is illustrated by simulation examples
In this paper, we propose two versions of a correlation-based blind source separation (BSS) method. ...
The separation of two unknown signals that mixed together in an unknown manner was shown to be possi...
International audienceThe paper introduces a new method for Blind Source Separation (BSS) in noisy i...
This paper deals with blind separation of spatially correlated signals mixed by an instantaneous sys...
Abstract The separation of unobserved sources from mixed observed data is a fundamental signal proce...
Most source separation algorithms are based on a model of stationary sources. However, it is a simpl...
Because it can be found in many applications, the Blind Separation of Sources (BSS) problem has rais...
Abstract. In this paper we present a methodology for blind source separation (BSS) based on a cohere...
We propose an algorithm for blind separation of sources in convolutive mixtures based on a subspace ...
In blind source separation problem it is usually assumed that the source signals are mutually indepe...
International audienceWe first propose a correlation-based blind source separation (BSS) method base...
In this paper we present a new method for separating non-stationary sources from their convolutive m...
We propose two types of correlation-based blind source separation (BSS) methods, i.e. a time-domain ...
In this paper, we address the problem of blind separation of spatially correlated signals, which is ...
Given a linear and instantaneous mixture model, we prove that for blind source separation (BSS) algo...
In this paper, we propose two versions of a correlation-based blind source separation (BSS) method. ...
The separation of two unknown signals that mixed together in an unknown manner was shown to be possi...
International audienceThe paper introduces a new method for Blind Source Separation (BSS) in noisy i...
This paper deals with blind separation of spatially correlated signals mixed by an instantaneous sys...
Abstract The separation of unobserved sources from mixed observed data is a fundamental signal proce...
Most source separation algorithms are based on a model of stationary sources. However, it is a simpl...
Because it can be found in many applications, the Blind Separation of Sources (BSS) problem has rais...
Abstract. In this paper we present a methodology for blind source separation (BSS) based on a cohere...
We propose an algorithm for blind separation of sources in convolutive mixtures based on a subspace ...
In blind source separation problem it is usually assumed that the source signals are mutually indepe...
International audienceWe first propose a correlation-based blind source separation (BSS) method base...
In this paper we present a new method for separating non-stationary sources from their convolutive m...
We propose two types of correlation-based blind source separation (BSS) methods, i.e. a time-domain ...
In this paper, we address the problem of blind separation of spatially correlated signals, which is ...
Given a linear and instantaneous mixture model, we prove that for blind source separation (BSS) algo...
In this paper, we propose two versions of a correlation-based blind source separation (BSS) method. ...
The separation of two unknown signals that mixed together in an unknown manner was shown to be possi...
International audienceThe paper introduces a new method for Blind Source Separation (BSS) in noisy i...