Computer Science ›› 2015, Vol. 42 ›› Issue (5): 149-152.doi: 10.11896/j.issn.1002-137X.2015.05.029

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Novel Blind Source Separation Algorithm Based on Givens Matrix and Joint Non-linear Uncorrelatedness

ZHAO Li-xiang and LIU Guo-qing   

  • Online:2018-11-14 Published:2018-11-14

Abstract: A novel algorithm based on Givens matrix and joint non-linear uncorrelatedness for blind source separation (BSS) where sources are statistically independent was proposed.Firstly,we measured independence with the joint non-linear uncorrelatedness of independent sources,since the measurement is the key to the effectiveness of the BSS algorithm.Secondly,based on the property that Givens matrices can impose the orthogonal constraint on the separation matrix and meanwhile decrease the number of parameters to be estimated by half approximately,we converted the BSS problem into an unconstrained optimization problem which is then solved by BFGS algorithm of quasi-Newton method.Finally,the separation for simulated mixed signals and real mixed voice signals shows the effectiveness of our algorithm.

Key words: Blind source separation,Independent component analysis,Non-linear uncorrelatedness,Givens matrix

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