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• W1502725260 abstract "Parameters estimations of periodic signals ( ) g t , where frequency of the investigated component is the key parameter, play a fundamental role in a variety of applications: impedance measurement, power quality estimation, radar, A/D testing, etc. The problem of evaluating the spectral performance of a given periodic signal reduces to the parameter estimation of each spectral component (frequency, amplitude, and phase) in the presence of noise. Estimation methods can be classified as parametric (D’Antona & Ferrero, 2006) and nonparametric (Agrež, 2002). Parametric methods are model-based and have very good selectivity and statistical efficiency, but require computationally intensive algorithms and very good ‘model agreement’ with a real multi-component signal. For this reason, such methods are unsuitable for many estimation problems. A better approach is to use nonparametric methods, which estimate the spectral parameters of interest by evaluating first the discrete Fourier transform (DFT) of the signal and then the parameters of the particular component. As we are dealing with periodic signals, the integral frequency transformation with the kernel j ft e− 2π is, in principle, the best approximation to periodicity of the signal. Analysis of the frequency spectrum provides the opportunity to see systematic periodicities in the presence of the reduced random noise by integration. Many of these estimations are based on coherent sampling; that is, on the accurate synchronization of the signal and the sampling rate, and on the collection of a number of samples belonging to an integer number of the signal periods. However, the normal situation for signal parameter estimation is non-coherent, or quasi-coherent sampling, and in such a sampled signal there can also be spurious components. When failing to observe an integer number of periods of even a single tone, the tone energy is spread over the whole frequency axis, and the leakage from neighboring components can significantly bias estimations of the component parameters." @default.
• W1502725260 created "2016-06-24" @default.
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• W1502725260 date "2012-04-11" @default.
• W1502725260 modified "2023-09-25" @default.
• W1502725260 title "Non-Parametric Estimation of the Periodic Signal Parameters in the Frequency Domain" @default.
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• W1502725260 doi "https://doi.org/10.5772/36168" @default.
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