Title :
What Can Make Joint Diagonalization Difficult?
Author_Institution :
Dept. of Appl. Math., Maryland Univ., College Park, MD, USA
Abstract :
We show that the issues of uniqueness and noise sensitivity in the problem of matrix joint diagonalization are closely related. We address other factors important in noise sensitivity. We distinguish between orthogonal and non-orthogonal joint diagonalization and argue that the latter can be more difficult than the former. Our analysis is based on the perturbation analysis of the stationary points of certain flows for joint diagonalization. Numerical experiments support the derived results.
Keywords :
blind source separation; matrix algebra; blind signal processing; matrix joint diagonalization; noise sensitivity; nonorthogonal joint diagonalization; perturbation analysis; Cost function; Educational institutions; Estimation error; Independent component analysis; Mathematics; Matrix decomposition; Sensitivity analysis; Signal processing algorithms; Symmetric matrices; Tensile stress; Blind Signal Processing; Independent Component Analysis; Joint Diagonalization; Sensitivity Analysis; Tensor Decomposition;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0727-3
DOI :
10.1109/ICASSP.2007.367102