In this paper, a novel approach to solve the permutation indeterminacy in the separation of convolved mixtures in frequency domain is proposed. A fixed-point algorithm in complex domain is used to separate the signals in each frequency bin. These are obtained applying a Short Time Fourier Transform on a set of fixed frames. To solve the ambiguity of the amplitude dilation, a simple method is proposed. The permutation indeterminacy is solved using an approach based on the Hungarian algorithm that solves an Assignment Problem and an algorithm of Dynamic Programming. To obtain the distances in the Assignment Problem, a Kullback-Leibler divergence is adopted. The results of the experiments, performed using both synthetic and benchmark data, allows us to conclude that the approach presents a good performance and permits to obtain a clear separation of the signals also when they are more than two.

Separation of Convolved Mixtures in Frequency Domain ICA

CIARAMELLA, Angelo;
2006

Abstract

In this paper, a novel approach to solve the permutation indeterminacy in the separation of convolved mixtures in frequency domain is proposed. A fixed-point algorithm in complex domain is used to separate the signals in each frequency bin. These are obtained applying a Short Time Fourier Transform on a set of fixed frames. To solve the ambiguity of the amplitude dilation, a simple method is proposed. The permutation indeterminacy is solved using an approach based on the Hungarian algorithm that solves an Assignment Problem and an algorithm of Dynamic Programming. To obtain the distances in the Assignment Problem, a Kullback-Leibler divergence is adopted. The results of the experiments, performed using both synthetic and benchmark data, allows us to conclude that the approach presents a good performance and permits to obtain a clear separation of the signals also when they are more than two.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/26045
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