Abstract

It is shown in this paper that an extended Prony time-frequency plane representation can be developed in a similar way to the one represented in other traditional non-stationary analysis methods, such as the Wigner-Ville distribution. To do this, the original Prony procedure is carried out in a series of time shifts through an array of data. The 'sliding window in time shifts approach' of the developed technique is closer to the short Fourier transform without its time-frequency resolution drawback. Also, it is argued here that the extended Prony time-frequency plane representation is suitable for noise filtering through a component exponential damping selection. The extended technique capacity of performing non-stationary analysis is compared with the pseudo-Wigner-Ville distribution, and its capacity of filtering noise is demonstrated.