Abstract
Spectral analysis is a Well-known and effective technique to understand random process and turbulence flow. For short data, however, the applicability is not clarified for the existing spectral analysis methods. This paper compares the spectral resolution and accuracy of the three methods of Blackman-Tukey (B-T), Discrete Fourier Transform (DFT) and Maximum Entropy Method (MEM) when applied to the five kinds of known random spectral data. It is found that MEM is best among these three methods and that the goodness of fit in the ensemble averaged power spectra by MEM can be improved by optimizing number of terms for large sample size.
