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Real Time Implementation of a Military Impulse Classifier

Rhudy, Matthew B (2010) Real Time Implementation of a Military Impulse Classifier. Master's Thesis, University of Pittsburgh. (Unpublished)

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A real time military impulse classifier has been developed to distinguish between impulsive events, such as artillery fire, and non-impulsive events, such as wind or aircraft noise. The classifier operates using an artificial neural network (ANN) with four scalar metrics as inputs. This classifier has been installed into two prototype noise monitoring systems, which are capable of establishing an accurate record of impulse events. This record can be used to assist in processing noise complaints and damage claims. The system continually monitors sound levels with a microphone array and activates when the sound level exceeds a given threshold. Once activated, the system processes the data to determine the classification, as well as the approximate bearing of the event.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Rhudy, Matthew
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairVipperman, Jeffery Sjsv@pitt.eduJSV
Committee MemberSlaughter, William Swss@engr.pitt.eduWSS
Committee MemberClark, William Wwclark@engr.pitt.eduWCLARK
Date: 26 January 2010
Date Type: Completion
Defense Date: 24 November 2009
Approval Date: 26 January 2010
Submission Date: 23 November 2009
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Mechanical Engineering
Degree: MSME - Master of Science in Mechanical Engineering
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: direction of arrival; DSP; impulse; localization; non impulse; non-impulse; nonimpulse; pc 104; pc/104; pc104; training; viper; classification; digital signal processing
Other ID:, etd-11232009-155759
Date Deposited: 10 Nov 2011 20:06
Last Modified: 15 Nov 2016 13:52


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