Document Type
Dissertation
Date of Award
Spring 6-30-1965
Degree Name
Doctor of Engineering Science in Electrical Engineering
Department
Electrical Engineering
First Advisor
P. A. Fox
Second Advisor
Joseph J. Padalino
Third Advisor
Frederick A. Russell
Abstract
The design of optimum polynomial digital data smoothers (filters) is considered for linear and adaptive processing systems. It is shown that a significant improvement in performance can be obtained by using linear smoothers that take into account known a priori constraints or distributions of the input signal. The procedure for designing optimum (minimum mean square error) adaptive polynomial data smoothers is then discussed and analyzed. The optimum smoother makes use of a priori signal statistics combined with an adaptive Bayesian weighting of a bank of conditionally optimum smoothers. Use of this technique permits large improvements in performance with a minimum of additonal system complexity.
Recommended Citation
Alterman, Stanley Bruce, "Optimum linear and adaptive polynomial smoothers" (1965). Dissertations. 1320.
https://digitalcommons.njit.edu/dissertations/1320
