[HTML][HTML] Relevance of polynomial matrix decompositions to broadband blind signal separation

S Redif, S Weiss, JG McWhirter - Signal processing, 2017 - Elsevier
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 …

Eigenvalue decomposition of a parahermitian matrix: Extraction of analytic eigenvectors

S Weiss, IK Proudler, FK Coutts… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
An analytic parahermitian matrix admits in almost all cases an eigenvalue decomposition
(EVD) with analytic eigenvalues and eigenvectors. We have previously defined a discrete …

Signal compaction using polynomial EVD for spherical array processing with applications

VW Neo, C Evers, S Weiss… - IEEE/ACM Transactions …, 2023 - ieeexplore.ieee.org
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 …

Eigenvalue decomposition of a parahermitian matrix: Extraction of analytic eigenvalues

S Weiss, IK Proudler, FK Coutts - IEEE Transactions on Signal …, 2021 - ieeexplore.ieee.org
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 …

Polynomial eigenvalue decomposition for multichannel broadband signal processing: a mathematical technique offering new insights and solutions

VW Neo, S Redif, JG McWhirter… - IEEE Signal …, 2023 - ieeexplore.ieee.org
This article is devoted to the polynomial eigenvalue decomposition (PEVD) and its
applications in broadband multichannel signal processing, motivated by the optimum …

On the existence and uniqueness of the eigenvalue decomposition of a parahermitian matrix

S Weiss, J Pestana, IK Proudler - IEEE Transactions on Signal …, 2018 - ieeexplore.ieee.org
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 …

Polynomial eigenvalue decomposition-based target speaker voice activity detection in the presence of competing talkers

VW Neo, S Weiss, SW McKnight… - … on Acoustic Signal …, 2022 - ieeexplore.ieee.org
Voice activity detection (VAD) algorithms are essential for many speech processing
applications, such as speaker diarization, automatic speech recognition, speech …

Scalable analytic eigenvalue extraction algorithm

FA Khattak, IK Proudler, S Weiss - IEEE Access, 2024 - ieeexplore.ieee.org
Broadband sensor array problems can be formulated using parahermitian polynomial
matrices, and the optimal solution to these problems can be based on the eigenvalue …

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 …

Enhancement of noisy reverberant speech using polynomial matrix eigenvalue decomposition

VW Neo, C Evers, PA Naylor - IEEE/ACM Transactions on …, 2021 - ieeexplore.ieee.org
Speech enhancement is important for applications such as telecommunications, hearing
aids, automatic speech recognition and voice-controlled systems. Enhancement algorithms …