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Least squares estimation of predictor coefficients from noisy observations

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2 Author(s)
Tomcik, J.D. ; University of Notre Dame, Notre Dame, Indiana ; Melsa, J.L.

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.

Published in:

Decision and Control including the 16th Symposium on Adaptive Processes and A Special Symposium on Fuzzy Set Theory and Applications, 1977 IEEE Conference on

Date of Conference:

7-9 Dec. 1977

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