Performance analysis of over-determined noisy ICA: Bayesian approach versus signal transformation

Wu, Yuanjia, Woo, Wai Lok and Dlay, Satnam (2008) Performance analysis of over-determined noisy ICA: Bayesian approach versus signal transformation. In: CSNDSP 08 - 6th International Symposium Communication Systems, Networks and Digital Signal Processing, 23rd - 25th July 2008, Graz, Austria.

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This paper proposes a new analysis on two robust methods for solving the blind source separation problem of noisy linear over-determined mixtures using 2-Stage ICA and Bayesian approach. A new method has also been developed to determine the optimal SNR threshold as the selection index for choosing the better method under the varying influence of the noise levels. An experimental simulation has been analytically conducted to verify the proposed method. An in-depth analysis has been carried out between the two methods regarding to their different performances through out the noise level from -10dB to 30dB. It is further shown that the threshold selection can be generalized to more complex cases that have the same ratio between the number of observed signals and the number of sources.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Bayesian analysis, Blind source separation, Extended ICA, Independent component analysis, Over-determined
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 28 May 2019 11:50
Last Modified: 10 Oct 2019 18:46

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