Discrimination Of Cylinders With Different Wall Thicknesses Using Neural Networks And Simulated Dolphin Sonar Signals
This paper describes a method integrating neural networks into a system for recognizing underwater objects. The system is based on a combination of simulated dolphin sonar signals, simulated auditory filters and artificial neural networks. The system is tested on a cylinder wall thickness difference...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.54.1765 2023-05-15T17:03:29+02:00 Discrimination Of Cylinders With Different Wall Thicknesses Using Neural Networks And Simulated Dolphin Sonar Signals Lars Nonboe Andersen Whitlow Au Jan Larsen Lars Kai Hansen The Pennsylvania State University CiteSeerX Archives 1999 application/postscript http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.54.1765 en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.54.1765 Metadata may be used without restrictions as long as the oai identifier remains attached to it. ftp://eivind.imm.dtu.dk/dist/1999/nonboe.nnsp99.ps.gz text 1999 ftciteseerx 2016-01-08T10:59:26Z This paper describes a method integrating neural networks into a system for recognizing underwater objects. The system is based on a combination of simulated dolphin sonar signals, simulated auditory filters and artificial neural networks. The system is tested on a cylinder wall thickness difference experiment and demonstrates high accuracy for small wall thickness differences. Results from the experiment are compared with results obtained by a false killer whale (pseudorca crassidens). Text Killer Whale Unknown |
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ftciteseerx |
language |
English |
description |
This paper describes a method integrating neural networks into a system for recognizing underwater objects. The system is based on a combination of simulated dolphin sonar signals, simulated auditory filters and artificial neural networks. The system is tested on a cylinder wall thickness difference experiment and demonstrates high accuracy for small wall thickness differences. Results from the experiment are compared with results obtained by a false killer whale (pseudorca crassidens). |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Lars Nonboe Andersen Whitlow Au Jan Larsen Lars Kai Hansen |
spellingShingle |
Lars Nonboe Andersen Whitlow Au Jan Larsen Lars Kai Hansen Discrimination Of Cylinders With Different Wall Thicknesses Using Neural Networks And Simulated Dolphin Sonar Signals |
author_facet |
Lars Nonboe Andersen Whitlow Au Jan Larsen Lars Kai Hansen |
author_sort |
Lars Nonboe Andersen |
title |
Discrimination Of Cylinders With Different Wall Thicknesses Using Neural Networks And Simulated Dolphin Sonar Signals |
title_short |
Discrimination Of Cylinders With Different Wall Thicknesses Using Neural Networks And Simulated Dolphin Sonar Signals |
title_full |
Discrimination Of Cylinders With Different Wall Thicknesses Using Neural Networks And Simulated Dolphin Sonar Signals |
title_fullStr |
Discrimination Of Cylinders With Different Wall Thicknesses Using Neural Networks And Simulated Dolphin Sonar Signals |
title_full_unstemmed |
Discrimination Of Cylinders With Different Wall Thicknesses Using Neural Networks And Simulated Dolphin Sonar Signals |
title_sort |
discrimination of cylinders with different wall thicknesses using neural networks and simulated dolphin sonar signals |
publishDate |
1999 |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.54.1765 |
genre |
Killer Whale |
genre_facet |
Killer Whale |
op_source |
ftp://eivind.imm.dtu.dk/dist/1999/nonboe.nnsp99.ps.gz |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.54.1765 |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
_version_ |
1766057359505883136 |