An iterative inversion approach to blind source separation

An Iterative Inversion Method For Blind Source Separation

An Iterative Eigendecomposition Approach to Blind Source Separation

In this work we address the generalized eigendecomposition approach (GED) to the blind source separation problem. We present an alternative formulation for GED based on the definition of congruent pencils. Making use of this definition, and matrix block operations, the eigendecompostion approach to blind source separation is completely characterized. We also present an iterative method to compu...

An Uniied Perspective of Blind Source Separation Adaptive Algorithms

Blind Source Separation (BSS) is an important topic in signal processing and neural networks where a lot of adaptive algorithms have been recently proposed. These algorithms, however, have been developed from many diierent points of view. This paper shows that most algorithms can be derived from a single guiding principle: the inversion of a nonlinear correlation matrix. The inversion is carrie...

A Time Domain Algorithm for Blind Separation of Convolutive Sound Mixtures and L1 Constrained Minimization of Cross Correlations

Abstract. A time domain blind source separation algorithm of convolutive sound mixtures is studied based on a compact partial inversion formula in closed form. An l1-constrained minimization problem is formulated to find demixing filter coefficients for source separation while capturing scaling invariance and sparseness of solutions. The minimization aims to reduce (lagged) cross correlations o...

An Iterative Blind Source Separation Method for Convolutive Mixtures of Images

The paper deals with blind source separation of images. The model which is adopted here is a convolutive multi-dimensional one. Recent results about polynomial matrices in several indeterminates are used to prove the invertibility of the mixing process. We then extend an iterative blind source separation method to the multi-dimensional case and show that it still applies if the source spectra v...