Structural health monitoring (SHM) is the main contributor of the future's smart city to deal
with the need for safety, lower maintenance costs, and reliable condition assessment of …

An analytic parahermitian matrix admits in almost all cases an eigenvalue decomposition
(EVD) with analytic eigenvalues and eigenvectors. We have previously defined a discrete …

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 …

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 …

This article is devoted to the polynomial eigenvalue decomposition (PEVD) and its
applications in broadband multichannel signal processing, motivated by the optimum …

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 …

In marine radar target detection, sea clutter will cause a large number of missed alarms and
false alarms, which will affect the accuracy of target detection. In order to suppress sea …

Voice activity detection (VAD) algorithms are essential for many speech processing
applications, such as speaker diarization, automatic speech recognition, speech …

Speech enhancement is important for applications such as telecommunications, hearing
aids, automatic speech recognition and voice-controlled systems. Enhancement algorithms …

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 …