Identification and extraction of individual modes in non-stationary multicomponent signals is a challenging task which is shared by several applications, like micro-doppler human gait analysis, surveillance or medical data analysis. State-of-the-art methods are not capable yet to correctly estimate individual modes if their instantaneous frequencies laws are not separable. The knowledge of time instants where modes interference occurs could represent a useful information to use in separation strategies. To this aim, a novel time-domain method that is capable of locating interferences is investigated in this paper. Its main property is the use of multiscale energy for selecting the best analysis scale without requiring either the use of time-frequency representations or imaging methods. The performance of the proposed method is evaluated through several numerical simulations and comparative studies with the state of the art Rényi entropy based method. Finally, an example concerning a potential application to simulated micro-doppler human gait data is provided.

A multiscale energy-based time-domain approach for interference detection in non-stationary signals / Bruni, Vittoria; Della Cioppa, L.; Vitulano, D.. - 12132:(2020), pp. 36-47. ((Intervento presentato al convegno 17th International Conference on Image Analysis and Recognition, ICIAR 2020 tenutosi a prt [10.1007/978-3-030-50516-5_4].

A multiscale energy-based time-domain approach for interference detection in non-stationary signals

Vittoria Bruni.;Della Cioppa L.
;
Vitulano D.
2020

Abstract

Identification and extraction of individual modes in non-stationary multicomponent signals is a challenging task which is shared by several applications, like micro-doppler human gait analysis, surveillance or medical data analysis. State-of-the-art methods are not capable yet to correctly estimate individual modes if their instantaneous frequencies laws are not separable. The knowledge of time instants where modes interference occurs could represent a useful information to use in separation strategies. To this aim, a novel time-domain method that is capable of locating interferences is investigated in this paper. Its main property is the use of multiscale energy for selecting the best analysis scale without requiring either the use of time-frequency representations or imaging methods. The performance of the proposed method is evaluated through several numerical simulations and comparative studies with the state of the art Rényi entropy based method. Finally, an example concerning a potential application to simulated micro-doppler human gait data is provided.
17th International Conference on Image Analysis and Recognition, ICIAR 2020
Human gait; Interferences detection; Multicomponent signal; Multiscale energy; Time-scale analysis
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
A multiscale energy-based time-domain approach for interference detection in non-stationary signals / Bruni, Vittoria; Della Cioppa, L.; Vitulano, D.. - 12132:(2020), pp. 36-47. ((Intervento presentato al convegno 17th International Conference on Image Analysis and Recognition, ICIAR 2020 tenutosi a prt [10.1007/978-3-030-50516-5_4].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1458440
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