Subject: concentration measures; dispersive channels; multivariate signals; non-stationary signals; multicomponent signal decomposition
Year: 2021
Type: Article
Title: Multivariate Decomposition of Acoustic Signals in Dispersive Channels
Author: Brajović, Miloš
Author: Stanković, Isidora
Author: Lerga, Jonatan
Author: Ioana, Cornel
Author: Zdravevski, Eftim
Author: Daković, Miloš
Abstract: We present a signal decomposition procedure, which separates modes into individual components while preserving their integrity, in effort to tackle the challenges related to the characterization of modes in an acoustic dispersive environment. With this approach, each mode can be analyzed and processed individually, which carries opportunities for new insights into their characterization possibilities. The proposed methodology is based on the eigenanalysis of the autocorrelation matrix of the analyzed signal. When eigenvectors of this matrix are properly linearly combined, each signal component can be separately reconstructed. A proper linear combination is determined based on the minimization of concentration measures calculated exploiting time-frequency representations. In this paper, we engage a steepest-descent-like algorithm for the minimization process. Numerical results support the theory and indicate the applicability of the proposed methodology in the decomposition of acoustic signals in dispersive channels.
Publisher: MDPI
Relation: Mathematics
Identifier: oai:repository.ukim.mk:20.500.12188/21380
Identifier: http://hdl.handle.net/20.500.12188/21380
