Linear prediction in cascade form

Abstract

The autocorrelation and covariance methods of linear prediction are formulated in terms of an inverse digital filter in cascade form, rather than the traditional direct form, to allow pole locations in the system model to be readily estimated and constrained. Iterative solution of the corresponding nonlinear normal equations is described. Applications to speech analysis and the compensation of biomedical signals are briefly discussed.