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

B. Chakraborty, V. Mahale, G. Navelkar, R. Desai
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引用次数: 1

Abstract

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.
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
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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