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A Generalization of Wiener Optimum Filtering and Prediction


Beutler, Fredrick Joseph (1957) A Generalization of Wiener Optimum Filtering and Prediction. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/D8FV-4255.


This work generalizes the Wiener-Kolmogorov theory of optimum linear filtering and prediction of stationary random inputs. It is assumed that signal and noise have passed through a random device before being available for filtering and prediction. A random device is a unit whose behavior depends on an unknown parameter for which an a priori probability distribution is given. Use of representation theorems and a Hilbert space structure make it possible to present the mathematical theory without the ambiguities encountered in engineering derivations. This approach also leads to a proof of the essential identity between the operator solution and a realizable lumped parameter filter. A number of engineering applications are cited. A few of these are worked out in some detail to illustrate the optimization procedure.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:(Engineering Science and Mathematics)
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Engineering
Minor Option:Mathematics
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • De Prima, Charles R.
Thesis Committee:
  • Unknown, Unknown
Defense Date:1 January 1957
Record Number:CaltechETD:etd-07082004-135353
Persistent URL:
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:2828
Deposited By: Imported from ETD-db
Deposited On:13 Jul 2004
Last Modified:13 Oct 2023 18:47

Thesis Files

PDF (Beutler_fj_1957.pdf) - Final Version
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