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    Study of effects of sonar bandwidth for underwater target classification, A

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    http://hdl.handle.net/10217/997
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    ECEmra00057.pdf (342.3Kb)
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    Abstract
    The problem of classifying underwater targets is addressed in this paper. The proposed classification system consists of several subsystems including preprocessing, subband decomposition using wavelet packets, linear predictive coding, feature selection and neural network classifier. A multi-aspect fusion system is introduced to further improve the classification accuracy. The classification performance of the overall system is demonstrated and benchmarked on two different acoustic backscattered data sets with 40- and 80-kHz bandwidth. A comprehensive study is then carried out to compare the ...
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    Author(s)
    Dobeck, Gerald J.; Jamshidi, Arta A.; Azimi-Sadjadi, Mahmood R.; Yao, De

    Date Issued
    2002
    Format
    born digital; articles
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    • Faculty Publications - Department of Electrical and Computer Engineering

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