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In this paper, we present a new multichannel spectral factorization algorithm which can be utilized to calculate the approximate spectral factor of any para-Hermitian polynomial matrix. The proposed algorithm is based on an iterative method for polynomial matrix eigenvalue decomposition (PEVD). By using the PEVD algorithm, the multichannel spectral factorization problem is simply broken down to a set of single channel problems which can be solved by means of existing one-dimensional spectral factorization algorithms. In effect, it transforms the multichannel spectral factorization problem into one which is much easier to solve.
|Title of host publication||2015 49th Asilomar Conference on Signals, Systems and Computers|
|Place of Publication||Piscataway, N.J.|
|Number of pages||5|
|Publication status||Published - 29 Feb 2016|
|Event||49th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, United States|
Duration: 8 Nov 2015 → 11 Nov 2015
|Conference||49th Asilomar Conference on Signals, Systems and Computers|
|Period||8/11/15 → 11/11/15|
- signal processing
- Hermitian matrices
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