State-space multitaper spectrogram algorithms : theory and applications
Name
971483377-MIT.pdf
Description
Full printable version
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838.4 KB
Format
Adobe PDF
Checksum (MD5)
2d4d1e04d343106bc6d670c0dd461f3b
Author(s)
Behr, Michael K
Advisor(s)
Emery N. Brown.
Date Issued
2016
Publisher
Massachusetts Institute of Technology
Abstract
I present the state-space multitaper approach for analyzing non-stationary time series. Nonstationary time series are commonly divided into small time windows for analysis, but existing methods lose predictive power by analyzing each window independently, even though nearby windows have similar spectral properties. The state-space multitaper algorithm combines two approaches for spectral analysis: the state-space approach models the relations between nearby windows, and the multitaper approach balances a bias-variance tradeoff inherent in Fourier analysis of finite interval data. I illustrate an application of the algorithm to real-time anesthesia monitoring, which could prevent traumatic cases of intraoperative awareness. I discuss issues including a real-time implementation and modeling the system's noise parameters. I identify the new problem of phase censorship, by which spectral leakage hides some information necessary to relate signal phases across windows in time.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
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 63-67).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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