In this paper, a method for signal component separation, operating in the Time-Frequency (TF) plane and employing a Turbo Estimation Algorithm (TEA), is described. A novel 2D distribution is proposed, named Two Window Spectrogram (TWS), which is free from crossterms and able to yield good time and frequency resolution. Then, a set of parameters is defined in the time-frequency plane, which are able to carry the relevant information on the signal components. An algorithm of estimation of these parameters is proposed, making use of a TEA scheme to yield improved performance. The algorithm has been tested by simulation, yielding very encouraging performance.

Identification of a multicomponent signal by a TEA scheme operating in the time-frequency plane / LO PRESTI, Letizia; Olmo, Gabriella; Galleani, Lorenzo. - STAMPA. - 3807:(1999), pp. 602-609. (Intervento presentato al convegno SPIE's 44th Annual Meeting tenutosi a Denver, Colorado, USA nel July 18-23, 1999) [10.1117/12.367676].

Identification of a multicomponent signal by a TEA scheme operating in the time-frequency plane

LO PRESTI, Letizia;OLMO, Gabriella;GALLEANI, LORENZO
1999

Abstract

In this paper, a method for signal component separation, operating in the Time-Frequency (TF) plane and employing a Turbo Estimation Algorithm (TEA), is described. A novel 2D distribution is proposed, named Two Window Spectrogram (TWS), which is free from crossterms and able to yield good time and frequency resolution. Then, a set of parameters is defined in the time-frequency plane, which are able to carry the relevant information on the signal components. An algorithm of estimation of these parameters is proposed, making use of a TEA scheme to yield improved performance. The algorithm has been tested by simulation, yielding very encouraging performance.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/1413301
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