Title :
Linear prediction, maximum flatness, maximum entropy, and AR polyspectral estimation
Author_Institution :
Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan
fDate :
6/1/1993 12:00:00 AM
Abstract :
The authors present a theoretical foundation for polyspectral estimation and modeling of non-Gaussian autoregressive (AR) processes which includes a new higher-order-statistics (HOS)-based linear prediction error filter and associated linear prediction polyspectral estimator, and a maximum higher order entropy polyspectral estimator, and considers the equivalences among these polyspectral estimators
Keywords :
entropy; filtering and prediction theory; parameter estimation; spectral analysis; statistical analysis; AR polyspectral estimation; higher-order-statistics; linear prediction error filter; linear prediction polyspectral estimator; maximum entropy; maximum flatness; nonGaussian autoregressive processes; Biomedical engineering; Entropy; Equations; Gaussian noise; Higher order statistics; Nonlinear filters; Parameter estimation; Predictive models; Signal processing; Speech processing;
Journal_Title :
Signal Processing, IEEE Transactions on
