[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 …
Properties and structure of the analytic singular value decomposition
S Weiss, IK Proudler, G Barbarino… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
We investigate the singular value decomposition (SVD) of a rectangular matrix of functions
that are analytic on an annulus that includes at least the unit circle. Such matrices occur, eg …
that are analytic on an annulus that includes at least the unit circle. Such matrices occur, eg …
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 …
MIMO signal processing in offset-QAM based filter bank multicarrier systems
Next-generation communication systems have to comply with very strict requirements for
increased flexibility in heterogeneous environments, high spectral efficiency, and agility of …
increased flexibility in heterogeneous environments, high spectral efficiency, and agility of …
Sequential matrix diagonalization algorithms for polynomial EVD of parahermitian matrices
For parahermitian polynomial matrices, which can be used, for example, to characterize
space-time covariance in broadband array processing, the conventional eigenvalue …
space-time covariance in broadband array processing, the conventional eigenvalue …
Signal compaction using polynomial EVD for spherical array processing with applications
Multi-channel signals captured by spatially separated sensors often contain a high level of
data redundancy. A compact signal representation enables more efficient storage and …
data redundancy. A compact signal representation enables more efficient storage and …
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 …
Polynomial eigenvalue decomposition for multichannel broadband signal processing: a mathematical technique offering new insights and solutions
This article is devoted to the polynomial eigenvalue decomposition (PEVD) and its
applications in broadband multichannel signal processing, motivated by the optimum …
applications in broadband multichannel signal processing, motivated by the optimum …
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 …
Design of FIR paraunitary filter banks for subband coding using a polynomial eigenvalue decomposition
The problem of paraunitary (PU) filter bank design for subband coding has received
considerable attention in recent years, not least because of the energy preserving property …
considerable attention in recent years, not least because of the energy preserving property …