Uniqueness Analysis of Non-Unitary Matrix Joint Diagonalization

Details Uniqueness Analysis of Non-Unitary Matrix Joint Diagonalization Uniqueness Analysis of Non-Unitary Matrix Joint Diagonalization

2011-11-30

arxiv.org/abs/1111.7088v3

Computer Science

Information Theory

23 pages

Scientific paper

Matrix Joint Diagonalization (MJD) is a powerful approach for solving the Blind Source Separation (BSS) problem. It relies on the construction of matrices which are diagonalized by the unknown demixing matrix. Their joint diagonalizer serves as a correct estimate of this demixing matrix only if it is uniquely determined. Thus, a critical question is under what conditions a joint diagonalizer is unique. In the present work we fully answer this question about the identifiability of MJD based BSS approaches and provide a general result on uniqueness conditions of matrix joint diagonalization. It unifies all existing results which exploit the concepts of non-circularity, non-stationarity, non-whiteness, and non-Gaussianity. As a corollary, we propose a solution for complex BSS, which can be formulated in a closed form in terms of an eigenvalue and a singular value decomposition of two matrices.

Affiliated with

Also associated with

No associations

Rating

Uniqueness Analysis of Non-Unitary Matrix Joint Diagonalization does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Uniqueness Analysis of Non-Unitary Matrix Joint Diagonalization, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Uniqueness Analysis of Non-Unitary Matrix Joint Diagonalization will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-7464