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基于遗传算法的神经网络被动声呐目标分类研究
引用本文: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, 17(4): 169-172
作者姓名:高翔  陈向东  宋爱国  陆佶人
作者单位:东南大学无线电工程系
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源泛化性能有明显提高。

关 键 词:声呐 目标分类 遗传算法 神经网络
收稿时间:1998-06-22
修稿时间:1998-09-02

Study on neural network classifier of passive sonar target based genetic algorithm
GAO Xiang,CHEN Xiang-dong,SONG Ai-guo and LU Ji-ren. Study on neural network classifier of passive sonar target based genetic algorithm[J]. Technical Acoustics, 1998, 17(4): 169-172
Authors:GAO Xiang  CHEN Xiang-dong  SONG Ai-guo  LU Ji-ren
Affiliation:Department of Radio Engineering, Southeast University, Nanjing 210018;Department of Radio Engineering, Southeast University, Nanjing 210018;Department of Radio Engineering, Southeast University, Nanjing 210018;Department of Radio Engineering, Southeast University, Nanjing 210018
Abstract: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.
Keywords:sonar   targets classification   genetic algorithm   neural network  
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