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Detection and diagnosis of parameters change in linear system using time-frequency transformation

A systematic optimization of the Cohen class time-frequency
transformation for detecting the parameters change is developed.
The local moments approach to change detection is proposed and a
general formula for the local moments is derived. The optimal
kernel functions of the time-frequency transformation are determined
based on the combined criteria of maximum sensitivity with respect to
parameters change and minimum distortion of physical interpretation
of the local moments. The sensitivity of the local moment with
respect to a certain kind of inputs is analyzed and a most "convenient"
and a "worst" input are identified. The results are presented in the
form of the case studies for detecting parameters change in simple
linear systems. / Graduation date: 1992

Identiferoai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/36264
Date16 September 1991
CreatorsPark, Dae-hyun
ContributorsKolodziej, W. J.
Source SetsOregon State University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

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