Efficient Sparse Blind Source Separation Algorithm for two- Channel Acoustic Noise Reduction

Shift-invariant Sparse Coding for Single Channel Blind Source Separation

In this paper we present results on single channel blind source separation based on a shift-invariant sparse coding model [1], [2] and [3]. This model learns a set of time-domain features from a single observation of the mixed signals. The found features can often be associated with a single source and can therefore be used to reconstruct the individual source signals. This is shown in this pap...

Single and Multi-Channel Noise Reduction Based on Blind Source Separation

Advances in telecommunications over the last few decades have made communications anywhere a reality. Technological progress has made communication systems reliable and affordable and mobile communication has now become ubiquitous. The freedom and flexibility provided by mobile communications introduces new challenges in the area of voice communication, an important one being the suppression of...

Engineering science Seismic Wavelet Signal Noise Reduction Algorithm of Blind Source Separation Optimization

In view of the existing seismic signal analysis model there are some problems is Analysis of the result is bad, the accuracy is not high. This paper puts forward an algorithm based on discrete wavelet and generalized the ICA model of seismic signal analysis. First for continuous Wavelet transform exists redundant of problem, on standard small wave transform algorithm of transform domain in the ...

Blind Source Separation via Multinode Sparse Representation

We consider a problem of blind source separation from a set of instantaneous linear mixtures, where the mixing matrix is unknown. It was discovered recently, that exploiting the sparsity of sources in an appropriate representation according to some signal dictionary, dramatically improves the quality of separation. In this work we use the property of multi scale transforms, such as wavelet or w...

Blind Source Separation via Multinode Sparse Representation