Implementation and Evaluation of Dispersion-Invariant Features for Signal Classification

Okopal, Greg (2007) Implementation and Evaluation of Dispersion-Invariant Features for Signal Classification. Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

When a sound wave interacts with an object, the acoustic energy may excite resonances in the object corresponding to its natural modes of vibration. The backscattered wave will then contain information which can be used to distinguish among different objects. As the wave propagates, it can be changed by the propagation channel, which complicates automatic classification of the echo. For example, in a dispersive channel, the duration of the wave increases with propagation distance. Our goal is to identify features of propagating waves that may be used for automatic classification. In this work, we implement and test a class of moment-like features that are invariant to specific propagation effects, in particular dispersion. Our tests of the classification utility of the "dispersion-invariant moments" (DIMS) are performed on numerical models of dispersive propagation and acoustic scattering from steel shells. We consider the case of real dispersion relations and in the conclusion discuss the implementation of complex dispersion and a future direction for research.

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Details

Item Type:	University of Pittsburgh ETD
Status:	Unpublished
Creators/Authors:	Creators Email Pitt Username ORCID Okopal, Greg gno1@pitt.edu GNO1
ETD Committee:	Title Member Email Address Pitt Username ORCID Committee Chair Loughlin, Patrick loughlin@engr.pitt.edu LOUGHLIN Committee Member El-Jaroudi, Amro amro@ee.pitt.edu AMRO Committee Member Boston, Robert boston@engr.pitt.edu BBN
Date:	12 June 2007
Date Type:	Completion
Defense Date:	14 December 2006
Approval Date:	12 June 2007
Submission Date:	26 March 2007
Access Restriction:	No restriction; Release the ETD for access worldwide immediately.
Institution:	University of Pittsburgh
Schools and Programs:	Swanson School of Engineering > Electrical Engineering
Degree:	MSEE - Master of Science in Electrical Engineering
Thesis Type:	Master's Thesis
Refereed:	Yes
Uncontrolled Keywords:	ocean acoustics; sonar; time-frequency analysis
Other ID:	http://etd.library.pitt.edu/ETD/available/etd-03262007-140932/, etd-03262007-140932
Date Deposited:	10 Nov 2011 19:32
Last Modified:	17 Apr 2023 14:37
URI:	http://d-scholarship.pitt.edu/id/eprint/6591

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