Bayesian Spectrum and Chirp Analysis
نویسندگان
چکیده
We seek optimal methods of estimating power spectrum and chirp (frequency change) rate for the case that one has incomplete noisy data on values y(t) of a time series. The Schuster periodogram turns out to be a \su cient statistic" for the spectrum, a generalization playing the same role for chirped signals. However, the optimal processing is not a linear ltering operation like the Blackman{Tukey smoothing of the periodogram, but a nonlinear operation. While suppressing noise/side lobe artifacts it achieves the same kind of improved resolution that the Burg method did for noiseless data.
منابع مشابه
Excerpts from Bayesian Spectrum Analysis and Parameter Estimation
Bayesian spectrum analysis is still in its infancy. It was born when E. T. Jaynes derived the periodogram 2] as a suucient statistic for determining the spectrum of a time sampled data set containing a single stationary frequency. Here we extend that analysis and explicitly calculate the joint posterior probability that multiple frequencies are present, independent of their amplitude and phase,...
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