A novel constrained multimodal approach for convolutive blind source separation is
presented which incorporates video information related to geometrical position of both the …

Blind deconvolution is an ill-posed problem. To solve such a problem, prior information,
such as, the sparseness of the source (ie, input) signal or channel impulse responses, is …

Cocktail party problem is a classical scientific problem that has been studied for decades.
Humans have remarkable skills in segregating target speech from a complex auditory …

A novel multimodal approach for independent component analysis (ICA) of complex valued
frequency domain signals is presented which utilizes video information to provide …

Blind separation of the electroencephalogram signals (EEGs) using topographic
independent component analysis (TICA) is an effective tool to group the geometrically …

Blind source separation, often called independent component analysis, is a main field of
research in signal processing since the eighties. It consists in retrieving the components, up …

The research reported in this thesis addresses the problem of component analysis, which
aims at reducing large data to lower dimensions, to reveal the essential structure of the data …

Methods and apparatuses for convolutive blind Source sepa ration are described. Each of a
plurality of input signals is transformed into frequency domain. Values of coefficients of …

An improvement in the multimodal approach to the problem of blind source separation (BSS)
of moving sources is proposed. The challenge of BSS for moving sources is that the mixing …