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Uniform FIR approximation of causal Wiener filters with applications to causal coherence

Author(s)
Barnes, Leighton P. (Leighton Pate)
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
George Verghese.
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M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
Leveraging the relationship between Wiener filtering and the coherence function, a version of coherence is defined that captures the causal relationship between WSS processes. This causal coherence is interpreted in a modeling context and used to demonstrate what a frequency dependent measure for causality both can and can't represent. To understand how well frequency dependent coherence spectra can be estimated with finite order approximations, the convergence of the FIR causal Wiener lters to the full IIR causal Wiener filter is investigated as filter length goes to infinity. The main results prove Lp convergence of the frequency responses for p = 1, 2, [infinity] under certain Hölder continuity conditions on the power spectra, as well as give asymptotic upper bounds for the convergence error. Keywords: Wiener lters, causality, coherence, FIR approximation
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
 
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
 
Cataloged from student-submitted PDF version of thesis.
 
Includes bibliographical references (pages 35-36).
 
Date issued
2015
URI
http://hdl.handle.net/1721.1/100295
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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