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Title: $Approaches for Checking Determinnancy in ICA-Based BSS
Abstract: In a blind signal separation problem,for the purpose of algorithm selection and results evaluation,it is important to check the determinacy of the observation matrix.To the best of our knowledge,there is no available way to tell the determined case from the underdetermined one under the condition of full rank.To overcome this problem,we propose two methods based on ICA(independent component analysis) for determinancy check.In the first approach,we check the determinancy by looking into the independency of the output signals estimated by ICA.In theory,the outputs won′t be independent in the underdetermined case,while in the determined case,the outputs will be independent if the source signals are independent.In the second approach,the observation data is windowed,and different windowed signal series are acquired by shifting the center of the rectangular window.when ICA is performed on the signal series,the basis vectors which are columns of the inverse of unmixing matrix are supposed to be stable in the determined case while unstable in the underdetermined case due to the variation of source signals' statistical distribution.Experimental results show that our methods achieved good performance.