| 基于小波包分解的导弹目标神经网络识别 |
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| 引用本文： | 张荣杰,张帅钦,张申涛.基于小波包分解的导弹目标神经网络识别[J].现代雷达,2012,34(2):77-80. |
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| 作者姓名： | 张荣杰 张帅钦 张申涛 |
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| 作者单位： | 解放军63610部队,新疆库尔勒,841001 |
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| 摘 要： | 提出了基于小波包分解特征的神经网络导弹目标识别算法。在该算法中,首先通过小波包分解获取能够反映时间序列时频信息的稳定特征,然后利用训练过的神经网络提取特征对导弹目标进行识别。文中运用一组仿真数据和一组试验数据对该算法进行测试,结果表明该算法具有较高的识别概率。
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| 关 键 词： | 目标散射截面 小波包分解 特征提取 神经网络 识别 |
Missile Target Recognition Algorithm of Neural Networks
Based on Wavelet Packet Decomposition |
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| ZHANG Rong-jie,ZHANG Shuai-qin and ZHANG Shen-tao.Missile Target Recognition Algorithm of Neural Networks
Based on Wavelet Packet Decomposition[J].Modern Radar,2012,34(2):77-80. |
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| Authors: | ZHANG Rong-jie ZHANG Shuai-qin and ZHANG Shen-tao |
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| Affiliation: | (Unit 63610 of PLA,Korla 841001,China) |
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| Abstract: | Missile target recognition algorithm of neural networks based on wavelet packet decomposition is presented.Firstly,stable feature is obtained by wavelet packet decomposition which can reflect the time-frequency information of time serials.Secondly, the feature which represents some target is identified by the trained neural networks.This algorithm is tested using artificial data and real data.The result indicates upper recognition probability. |
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| Keywords: | radar cross section wavelet packet decomposition feature extraction neural networks recognition |
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