separation with dereverberation-based pre-processing incorporating visual cues.

This paper considers the underdetermined blind separation of multiple input multiple output (MIMO) radar signals that are insufficiently sparse in both time and frequency domains under noisy conditions, while traditional algorithms are usually applied in the ideal sparse environment. An effective separation method based on single source point (SSP) identification and time-frequency smoothed l0 ...

Blind source separation is an important task for applications in biomedical engineering, signal proo cessing and communications. In order to get too wards on-line time-variant applications, the converr gence speed of a separation algorithm has to be fast enough to track the changes of the environment. In this paper, a two-stage algorithm for blind source separation of convolutive mixtures in ca...

In this paper we consider the problem of separating different sound sources in multichannel audio signals. Different approaches to the problem of Blind Source Separation (BSS), e.g. the Independent Component Analysis (ICA) originally proposed by Herault and Jutten, and extensions to this including delays, work fine for artificially mixed signals. However the quality of the separated signals is ...

In this article, we present a two-stage blind source separation (BSS) algorithm for robot audition. The first stage consists in a fixed beamforming preprocessing to reduce the reverberation and the environmental noise. Since we are in a robot audition context, the manifold of the sensor array in this case is hard to model due to the presence of the head of the robot, so we use pre-measured head...

On-line solid phase extraction (SPE) based on  nano adsorbent for pre-concentration of inorganic arsenic in water and waste water samples was developed prior to determine by hydride generation atomic absorption spectrometry (HG-AAS). By hydride generation simulation system (HGSS), the  inorganic arsenic in liquid samples changed to hydride form and pass through nano platinum multi wall carbon n...

Independent component analysis or blind source separation is a new technique of extracting independent signals from mixtures. It is applicable even when the number of independent sources is unknown and is larger or smaller than the number of observed mixture signals. This article extends the natural gradient learning algorithm to be applicable to these overcomplete and undercomplete cases. Here...