Evolutionary maximum entropy spectral analysis

  • Authors:

  • S. I. Shah;L. F. Chaparro;A. S. Kayhan

  • Affiliations:

  • Dept. of Electr. Eng., Pittsburgh Univ., PA, USA;Dept. of Electr. Eng., Pittsburgh Univ., PA, USA;Dept. of Electr. Eng., Pittsburgh Univ., PA, USA

  • Venue:
  • ICASSP '94 Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04
  • Year:
  • 1994

Quantified Score

Hi-index 0.00

Visualization

Abstract

We extend maximum entropy (ME) spectral analysis to non-stationary signals using the theory of the Wold-Cramer evolutionary spectrum. The evolutionary maximum entropy (EME) problem reduces to the fitting of a time-varying autoregressive model to the Fourier coefficients of the evolutionary spectrum. The model parameters are efficiently found by means of the Levinson algorithm. In the non-stationary case it is not the autocorrelation function that provides the appropriate data for the EME analysis, but rather the Fourier coefficients of the evolutionary spectrum. An estimator of these coefficients is proposed. By means of examples we show the EME estimator provides higher frequency resolution and better sidelobe behavior than existing estimators of the evolutionary spectrum.