In this paper, we present a specific algorithm for the blind identification of a two input two output system. A closed form solution for the blind identification of the system is de-rived by exploiting the temporal coherence properties of the input sources. By exploiting the inherent indeterminacies of the blind processing, a simplified version is derived making the algorithm computationally cheaper and more suitable for hardware implementation. The weights of the zero forcing blind separator are then deduced. The performance of the pro-posed solutions with respect to the signal to noise ratio (SNR) and sample size are provided in the simulation section. 1
In this thesis, we focus on the signal processing foundations of this emerging field of fundamental ...
This paper addresses the blind source separation problem for the case where more sensors than source...
Abstract—Blind source separation (BSS) aims to recover a set of statistically independent source sig...
Abstract—Blind system identification and subspace tracking represent two important classes of signal...
This paper deals with the problem of blind identification and source separation which consists of es...
In this paper, we present a new approach for the blind source separation problem. Recently, several ...
In this paper, a new approach for blind system identification is presented. Our model involves a sin...
The problem of blind identification of source signals is to estimate the source signals without know...
Blind identification is a crucial subtask in signal processing problems such as blind signal separat...
Abstract—Blind identification is a crucial subtask in signal processing problems such as blind signa...
This paper addresses the blind source separation problem for the case where more sensors than source...
International audienceIn this paper, we propose analytical formulas that involve second order statis...
In this paper a fast method for blind identification of periodic sources is presented. In the well-k...
Blind Source Separation is a modern signal processing technique which recovers boththe unknown sourc...
Blind identification of spatial mixtures allows an array of sensors to implement source separation w...
In this thesis, we focus on the signal processing foundations of this emerging field of fundamental ...
This paper addresses the blind source separation problem for the case where more sensors than source...
Abstract—Blind source separation (BSS) aims to recover a set of statistically independent source sig...
Abstract—Blind system identification and subspace tracking represent two important classes of signal...
This paper deals with the problem of blind identification and source separation which consists of es...
In this paper, we present a new approach for the blind source separation problem. Recently, several ...
In this paper, a new approach for blind system identification is presented. Our model involves a sin...
The problem of blind identification of source signals is to estimate the source signals without know...
Blind identification is a crucial subtask in signal processing problems such as blind signal separat...
Abstract—Blind identification is a crucial subtask in signal processing problems such as blind signa...
This paper addresses the blind source separation problem for the case where more sensors than source...
International audienceIn this paper, we propose analytical formulas that involve second order statis...
In this paper a fast method for blind identification of periodic sources is presented. In the well-k...
Blind Source Separation is a modern signal processing technique which recovers boththe unknown sourc...
Blind identification of spatial mixtures allows an array of sensors to implement source separation w...
In this thesis, we focus on the signal processing foundations of this emerging field of fundamental ...
This paper addresses the blind source separation problem for the case where more sensors than source...
Abstract—Blind source separation (BSS) aims to recover a set of statistically independent source sig...