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| 一种基于模糊神经网的超短波信号自动识别算法 | |
| 引用本文： | 刘茂. 一种基于模糊神经网的超短波信号自动识别算法[J]. 成都信息工程学院学报, 2007, 22(5): 588-592 |
| 作者姓名： | 刘茂 |
| 作者单位： | 军械工程学院,河北,石家庄,050000 |
| 摘 要： | 针对具体的军用超短波信号,提出一种基于模糊神经网的改进信号识别算法.该算法利用模糊神经网实现模糊推理系统,采用分步识别的方法,将特征参数映射到模糊空间进行二分类.仿真表明:在具有高斯加性白噪声的环境中,信噪比高于15dB时,系统识别率高于95%. |
| 关 键 词： | 调制 特征参数 模式识别 基于模糊 神经网 超短波 信号 自动 识别算法 fuzzy neural network base signal scheme 识别率 推理系统 信噪比 环境 加性白噪声 高斯 仿真 二分类 模糊空间 参数映射 |
| 文章编号： | 1671-1742（2007）05-0588-05 |
| 收稿时间： | 2007-05-21 |
| 修稿时间： | 2007-06-06 |
A recognition scheme of ultra-short signal base on fuzzy neural network |
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| LIU Mao. A recognition scheme of ultra-short signal base on fuzzy neural network[J]. Journal of Chengdu University of Information Technology, 2007, 22(5): 588-592 | |
| Authors: | LIU Mao |
| Affiliation: | Ordrtance Engineering College, Shijiazhuang 050000, China |
| Abstract: | An improved recognition arithmetic based on the fuzzy neural network is presented for the ultra-short signal used in the martial communications. This arithmetic forms an fuzzy illation system with the neural network, mapping the characters to the fuzzy space in order to classify the characters into two species. The simulation shows that all the ultra-short signals are classified with success rate more than 95% when SNR is higher than 15dB. |
| Keywords: | modulation characters pattern recognition |
| 本文献已被 维普 万方数据 等数据库收录！ | |