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单水滴致噪声平均能量密度谱的神经网络模型
引用本文:曹伟国,张春玲,张卫强,王振峰.单水滴致噪声平均能量密度谱的神经网络模型[J].海洋测绘,2012(1):14-17.
作者姓名:曹伟国  张春玲  张卫强  王振峰
作者单位:[1]海军东海舰队海洋水文气象中心,浙江宁波315122 [2]中国海洋大学,山东青岛266100
摘    要:单水滴击水致水下噪声平均能量密度谱是Medwin雨致噪声理论中的基本参量。基于人工神经网络算法,建立了利用一定粒度分布的水滴群及其击水后的噪声谱反演单水滴致水下噪声能量密度谱的模型。通过分析三种训练模式,得到反演值与真实值的对比及误差指标MSE的起伏性和收敛速度,验证了利用人工神经网络算法研究雨致噪声的有效性。

关 键 词:雨致噪声  粒度分布  噪声谱  平均能量密度谱  人工神经网络

The Neural Networks Algorithm of the Average Energy SpectralDensity of Underwater Noise for a Given Single Waterdrop
CAO Weiguo,ZHANG Chunling,ZHANG Weiqiang,WANG Zhenfeng.The Neural Networks Algorithm of the Average Energy SpectralDensity of Underwater Noise for a Given Single Waterdrop[J].Hydrographic Surveying and Charting,2012(1):14-17.
Authors:CAO Weiguo  ZHANG Chunling  ZHANG Weiqiang  WANG Zhenfeng
Institution:1.Ocean Hydrometeorology Institute,Navy Donghai-Armada,Ningbo 315122,China;2.Ocean University of China,Qingdao 266100,China)
Abstract:The average energy spectral density of underwater noise for a given single waterdrop is the basic parameter of rain noise theory proposed by Medwin.The neural networks model is constructed to calculate the average energy noise spectral density for a single waterdrop by noise spectral levels caused by a swarm of waterdrops with confirmed drop-size distribution.It is proved to be effective by the comparison of the calculated data with the laboratorial data and the characters of the MSE through three different training models.
Keywords:rain noise  drop-size distribution  noise spectral  average energy spectral density  neural networks
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