Least squares estimation of predictor coefficients from noisy observations

A new method for estimating predictor coefficients (autoregressive parameters) based on noisy observations is presented. Least squares estimation methodology is used. Autoregressive parameters for the noisy observations are identified and used to find the desired autoregressive parameters. The particular application of concern is the digital processing of noisy speech.