The general problem of separating multiple sources mixed into a single channel is illposed; in order to solve it, additional constraints must be applied. One very general class of constraints is prior knowledge of the source signals: limitations on the waveforms possible for each source can disambiguate the mixture since there may only be one set of ‘legal’ source signals that would add togethe...

Separation and localisation of P300 sources and their constituent subcomponents for both visual and audio stimulations is investigated in this paper. An effective constrained blind source separation (CBSS) algorithm is developed for this purpose. The algorithm is an extension of the Infomax BSS system for which a measure of distance between a carefully measured P300 and the estimated sources is...

We present a multiple antenna system for industrial, scientific, and medical (ISM)-band transmission (MASI). The hardware demonstrator was developed and realized at our institute. It enables multiple-input multiple-output (MIMO)-communication applications and is capable of transmiting arbitrary signals using 8 transmit and 8 receive antennas in parallel. It operates in the 2.4GHz ISM-band. The ...

This paper presents a method for solving the permutation problem of frequency domain blind source separation (BSS) when the number of source signals is large, and the potential source locations are omnidirectional. We propose a combination of small and large spacing sensor pairs with various axis directions in order to obtain proper geometric information for solving the permutation problem. Exp...

Recognition of planar objects from their images taken from different viewpoints requires affine invariants calculated from the object boundaries. The equivalence between affine transformation and the source mixture model simplifies the recognition problem. The rotation, scaling, skewing, and translation effects of the affine transformation can be undone by using blind source separation (BSS) te...

This paper discusses some theoritical results on underdetermined source separation i.e. when the mixing matrix is degenerate, espcially when there is more sources than observations. In this case, we show that the sources can be restored up to an arbitrary additive random vector. In the particular case of discrete sources, very relevant for digital communications, we show that this vector is cer...

We demonstrate that selective attention can improve learning. Considerably fewer samples are needed to learn a source separation problem when the inputs are pre-segmented by the proposed model. The model combines biased-competition model for attention with a habituation mechanism which allows the focus of attention to switch from one object to another. The criteria for segmenting objects are es...

This paper introduces the audio part of the 2010 communitybased Signal Separation Evaluation Campaign (SiSEC2010). Seven speech and music datasets were contributed, which include datasets recorded in noisy or dynamic environments, in addition to the SiSEC2008 datasets. The source separation problems were split into five tasks, and the results for each task were evaluated using different objecti...