[HTML][HTML] Relevance of polynomial matrix decompositions to broadband blind signal separation
The polynomial matrix EVD (PEVD) is an extension of the conventional eigenvalue
decomposition (EVD) to polynomial matrices. The purpose of this article is to provide a …
decomposition (EVD) to polynomial matrices. The purpose of this article is to provide a …
Eigenvalue decomposition of a parahermitian matrix: Extraction of analytic eigenvectors
An analytic parahermitian matrix admits in almost all cases an eigenvalue decomposition
(EVD) with analytic eigenvalues and eigenvectors. We have previously defined a discrete …
(EVD) with analytic eigenvalues and eigenvectors. We have previously defined a discrete …
Eigenvalue decomposition of a parahermitian matrix: Extraction of analytic eigenvalues
An analytic parahermitian matrix admits an eigenvalue decomposition (EVD) with analytic
eigenvalues and eigenvectors except in the case of multiplexed data. In this paper, we …
eigenvalues and eigenvectors except in the case of multiplexed data. In this paper, we …
On the existence and uniqueness of the eigenvalue decomposition of a parahermitian matrix
This paper addresses the extension of the factorization of a Hermitian matrix by an
eigenvalue decomposition (EVD) to the case of a parahermitian matrix that is analytic at …
eigenvalue decomposition (EVD) to the case of a parahermitian matrix that is analytic at …
Space-time covariance matrix estimation: Loss of algebraic multiplicities of eigenvalues
FA Khattak, S Weiss, IK Proudler… - 2022 56th Asilomar …, 2022 - ieeexplore.ieee.org
Parahermitian matrices in almost all cases admit an eigenvalue decomposition (EVD) with
analytic eigenvalues. This decomposition is key in order to extend the utility of the EVD from …
analytic eigenvalues. This decomposition is key in order to extend the utility of the EVD from …
Row-shift corrected truncation of paraunitary matrices for PEVD algorithms
J Corr, K Thompson, S Weiss… - 2015 23rd European …, 2015 - ieeexplore.ieee.org
In this paper, we show that the paraunitary (PU) matrices that arise from the polynomial
eigenvalue decomposition (PEVD) of a parahermitian matrix are not unique. In particular …
eigenvalue decomposition (PEVD) of a parahermitian matrix are not unique. In particular …
Compact order polynomial singular value decomposition of a matrix of analytic functions
MA Bakhit, FA Khattak, IK Proudler… - 2023 IEEE 9th …, 2023 - ieeexplore.ieee.org
This paper presents a novel method for calculating a compact order singular value
decomposition (SVD) of polynomial matrices, building upon the recently proven existence of …
decomposition (SVD) of polynomial matrices, building upon the recently proven existence of …
Iterative approximation of analytic eigenvalues of a parahermitian matrix EVD
We present an algorithm that extracts analytic eigenvalues from a parahermitian matrix.
Operating in the discrete Fourier transform domain, an inner iteration re-establishes the lost …
Operating in the discrete Fourier transform domain, an inner iteration re-establishes the lost …
Second order sequential best rotation algorithm with householder reduction for polynomial matrix eigenvalue decomposition
The Second-order Sequential Best Rotation (SBR2) algorithm, used for Eigenvalue
Decomposition (EVD) on para-Hermitian polynomial matrices typically encountered in …
Decomposition (EVD) on para-Hermitian polynomial matrices typically encountered in …
Multiple shift second order sequential best rotation algorithm for polynomial matrix EVD
Z Wang, JG McWhirter, J Corr… - 2015 23rd European …, 2015 - ieeexplore.ieee.org
In this paper, we present an improved version of the second order sequential best rotation
algorithm (SBR2) for polynomial matrix eigenvalue decomposition of para-Hermitian …
algorithm (SBR2) for polynomial matrix eigenvalue decomposition of para-Hermitian …