Sonar discrimination of cylinders from different angles using neural networks neural networks

Lars Nonboe Andersen, Whiwlow Au, Jan Larsen, Lars Kai Hansen

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    Abstract

    This paper describes an underwater object discrimination system applied to recognize cylinders of various compositions from different angles. The system is based on a new combination of simulated dolphin clicks, simulated auditory filters and artificial neural networks. The model demonstrates its potential on real data collected from four different cylinders in an environment where the angles were controlled in order to evaluate the models capabilities to recognize cylinders independent of angles.
    Original languageEnglish
    Title of host publicationProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
    Volume2
    PublisherIEEE
    Publication date1999
    Pages1121-1124
    ISBN (Print)0-7803-5041-3
    DOIs
    Publication statusPublished - 1999
    EventIEEE International Conference on Acoustics, Speech, and Signal Processing 1999 - Phoenix, AZ, United States
    Duration: 15 Mar 199919 Mar 1999
    http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6110

    Conference

    ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing 1999
    CountryUnited States
    CityPhoenix, AZ
    Period15/03/199919/03/1999
    Internet address

    Bibliographical note

    Copyright: 2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

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