A spectral estimation algorithm based on minimum cross entropy method

Autor: T. Wada, S. Sugimoto, Ken Nakamuro
Rok vydání: 2003
Předmět:
Zdroj: Proceedings of the 41st SICE Annual Conference. SICE 2002..
DOI: 10.1109/sice.2002.1195466
Popis: 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 (1975), 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.
Databáze: OpenAIRE