利用声波后向散射回波波形进行海底分类——人工神经网络的应用

OCEANS 2006 - Asia Pacific Pub Date : 2006-05-01 DOI:10.1109/OCEANSAP.2006.4393981

B. Chakraborty, V. Mahale, G. Navelkar, R. Desai

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引用次数: 1

摘要

本文设计了基于人工神经网络(ANN)的海底分类系统。本文采用的人工神经网络架构是自组织特征映射(SOFM)和线性向量量化(LVQ1)的结合。本文分析了目前在印度西部大陆架中部12个海底沉积物位置用单波束测深仪采集的回波波形数据，并介绍了该分类器的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Seafloor Classification Using Acoustic Backscatter Echo-waveform - Artificial Neural Network Applications

In this paper seafloor classifications system based on artificial neural network (ANN) has been designed. The ANN architecture employed here is a combination of self organizing feature map (SOFM) and linear vector quantization (LVQ1). Currently acquired echo-waveform data acquired using single beam echo-sounder from twelve seafloor sediment locations from central part of the western continental shelf of India is analyzed and performance of the classifier is presented in this paper.

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来源期刊

OCEANS 2006 - Asia Pacific

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