文章摘要
高翔,陈向东,宋爱国,陆佶人.基于遗传算法的神经网络被动声呐目标分类研究[J].声学技术,1998,(4):169~172
基于遗传算法的神经网络被动声呐目标分类研究
Study on neural network classifier of passive sonar target based genetic algorithm
投稿时间:1998-06-22  修订日期:1998-09-02
DOI:
中文关键词: 声呐  目标分类  遗传算法  神经网络
英文关键词: sonar  targets classification  genetic algorithm  neural network
基金项目:
作者单位
高翔 东南大学无线电工程系, 南京 210018 
陈向东 东南大学无线电工程系, 南京 210018 
宋爱国 东南大学无线电工程系, 南京 210018 
陆佶人 东南大学无线电工程系, 南京 210018 
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中文摘要:
      被动声呐目标识别系统中目标分类器的设计和训练是一项重要内容.本文设计了目标分类器的神经网络结构,提出了一种用改进的遗传算法训练神经网络分类器的新方法.最后,对海上实录的A、B、C三类目标噪声进行了分类识别,实验结果表明基于遗传算法的神经网络分类器比传统的基于BP算法的神经网络分类器泛化性能有明显提高.
英文摘要:
      The targets classifier is a key element in passive Sonar target recognition systems.In this paper,the structure of neural network targets classifier is designed.We proposed a novel method for training neural network targets classifier by using an improved Genetic Algorithm (GA).The targets classifier is used to classify three different classes of targets:A,B and C.The result of experiment shows that the preformance of GA based neural network targets classifier is better than that of Back propagation algorithm based neural network targets classifier.
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