DocumentCode :
1919748
Title :
Amplitude and permutation indeterminacies in frequency domain convolved ICA
Author :
Ciaramella, Angelo ; Tagliaferri, Roberto
Author_Institution :
Dept. of Math. & Comput. Sci., Salerno Univ., Italy
Volume :
1
fYear :
2003
fDate :
20-24 July 2003
Firstpage :
708
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 to perform the separation of the signals for each frequency domain is used. To obtain the frequency bins a short time Fourier transform on a set of fixed frames, is considered. 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. We shall see that this approach presents a good performance and permits to obtain a clear separation of the signals.
Keywords :
Fourier transforms; blind source separation; convolution; dynamic programming; frequency-domain analysis; independent component analysis; Hungarian algorithm; Kullback-Leibler divergence; amplitude indeterminacy; assignment problem; dynamic programming; fixed frames; fixed-point algorithm; frequency domain convolved ICA; permutation indeterminacy; short time Fourier transform; Computer science; Convolution; Data models; Deconvolution; Finite impulse response filter; Fourier transforms; Frequency domain analysis; IIR filters; Independent component analysis; Mathematics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
ISSN :
1098-7576
Print_ISBN :
0-7803-7898-9
Type :
conf
DOI :
10.1109/IJCNN.2003.1223454
Filename :
1223454
Link To Document :
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