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IDA
2009
Springer

On Optimal Selection of Correlation Matrices for Matrix-Pencil-Based Separation

10 years 7 months ago
On Optimal Selection of Correlation Matrices for Matrix-Pencil-Based Separation
Abstract. The Matrix-Pencil approach to blind source separation estimates the mixing matrix from the Generalized Eigenvalue Decomposition (GEVD), or Exact Joint Diagonalization, of two “target-matrices”. In a Second-Order-Statistics framework, these target-matrices are two different correlation matrices (e.g., at different lags, taken over different time-intervals, etc.), attempting to capture the diversity of the sources (e.g., diverse spectra, different nonstationarity profiles, etc.). A central question in this context is how to best choose these target-matrices, given a statistical model for the sources. To answer this question, we consider a general paradigm for the target-matrices, viewed as two “generalized correlation” matrices, whose structure is governed by two selected “Association-Matrices”. We then derive an explicit expression (assuming Gaussian sources) for the resulting Interference-to-Source Ratio (ISR) in terms of the Association-Matrices. Subsequentl...
Arie Yeredor
Added 26 May 2010
Updated 26 May 2010
Type Conference
Year 2009
Where IDA
Authors Arie Yeredor
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