A real-time neural-net computing approach to the detection and classification of underwater acoustic transients

Bibliographic Details
Main Author:	Hemminger, Thomas Lee
Language:	English
Published:	Case Western Reserve University School of Graduate Studies / OhioLINK 1992
Subjects:	real-time neural-net computing approach detection classification underwater acoustic transients
Online Access:	http://rave.ohiolink.edu/etdc/view?acc_num=case1056044506

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spelling	ndltd-OhioLink-oai-etd.ohiolink.edu-case10560445062021-08-03T05:30:45Z A real-time neural-net computing approach to the detection and classification of underwater acoustic transients Hemminger, Thomas Lee real-time neural-net computing approach detection classification underwater acoustic transients Underwater acoustic transients can develop from a variety of sources ranging from the cry of a whale to the sound of a torpedo launch. Accordingly, detection and classification of such transients by automated means can be an exceedingly difficult task. This thesis describes the design and implementation of a new approach to this problem based on adaptive pattern recognition employing neural networks and additional techniques including the Hausdorff metric. This system uses self-organization to both generalize and provide rapid throughput while, in addition, utilizing supervised learning for decision making. The design is based on a concept which temporally partitions acoustic transient signals, and as a result, studies their trajectories through power spectral density space. This method has exhibited a high rate of success for a large set of underwater transients contained in both quiet and noisy ocean environments, and is capable of real-time operation. 1992 English text Case Western Reserve University School of Graduate Studies / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=case1056044506 http://rave.ohiolink.edu/etdc/view?acc_num=case1056044506 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection	NDLTD
language	English
sources	NDLTD
topic	real-time neural-net computing approach detection classification underwater acoustic transients
spellingShingle	real-time neural-net computing approach detection classification underwater acoustic transients Hemminger, Thomas Lee A real-time neural-net computing approach to the detection and classification of underwater acoustic transients
author	Hemminger, Thomas Lee
author_facet	Hemminger, Thomas Lee
author_sort	Hemminger, Thomas Lee
title	A real-time neural-net computing approach to the detection and classification of underwater acoustic transients
title_short	A real-time neural-net computing approach to the detection and classification of underwater acoustic transients
title_full	A real-time neural-net computing approach to the detection and classification of underwater acoustic transients
title_fullStr	A real-time neural-net computing approach to the detection and classification of underwater acoustic transients
title_full_unstemmed	A real-time neural-net computing approach to the detection and classification of underwater acoustic transients
title_sort	real-time neural-net computing approach to the detection and classification of underwater acoustic transients
publisher	Case Western Reserve University School of Graduate Studies / OhioLINK
publishDate	1992
url	http://rave.ohiolink.edu/etdc/view?acc_num=case1056044506
work_keys_str_mv	AT hemmingerthomaslee arealtimeneuralnetcomputingapproachtothedetectionandclassificationofunderwateracoustictransients AT hemmingerthomaslee realtimeneuralnetcomputingapproachtothedetectionandclassificationofunderwateracoustictransients
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A real-time neural-net computing approach to the detection and classification of underwater acoustic transients

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