The Burg's algorithm was applied to the spectral analysis of a signal that is the sum of 11 sinusoids as intermixed with different noise levels. Particular attention was paid to those features that for single sinusoids represent the crucial point of this technique and it was found that, for a multicomponent signal, the frequency shiftings are smaller than for single sinusoids and the splitting phenomena tend to occur at much higher orders of the prediction error filter. For a noise power smaller than 17% of the power of the lowest amplitude component, all the expected peaks were easily identified and most of the power was concentrated in very narrow ranges of frequency.

Maximum entropy spectral analysis of artificial sinusoidal signals

Vellante M.;U. Villante
1984

Abstract

The Burg's algorithm was applied to the spectral analysis of a signal that is the sum of 11 sinusoids as intermixed with different noise levels. Particular attention was paid to those features that for single sinusoids represent the crucial point of this technique and it was found that, for a multicomponent signal, the frequency shiftings are smaller than for single sinusoids and the splitting phenomena tend to occur at much higher orders of the prediction error filter. For a noise power smaller than 17% of the power of the lowest amplitude component, all the expected peaks were easily identified and most of the power was concentrated in very narrow ranges of frequency.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11697/6883
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