A Spectral Estimation Algorithm based on Minimum Cross Entropy Method

Abstract

The minimum cross entropy (MCE) spectral analysis method is able to incorporate a prior information of spectra into the spectral analysis. Applying the principle of the MCE, the authors proposed a continuous spectral estimation method (C-MCEM) for stationary time series with a prior spectrum generated by AR models under the observation of the autocorrelation values. In this paper, combining the C-MCEM with the Burg algorithm, we derive a new spectral estimation algorithm where the time series data as well as a prior spectrum are utilized. Applying the proposed method to sound data, we also show the spectral estimation results.