General Mathematics

   

基于证据聚类的水声目标识别算法研究

Authors: 张扬, 杨建华, 侯宏

摘 要:针对水声目标信号复杂、样本获取难度大且富含不确定信息的问题,研究了一种证据聚类识 别算法。首先在水声目标的各类训练样本中,根据特征距离大小选取待识别目标的K 近邻,并采用证 据近邻分类优化算法为各目标数据构造一组合理的初始基本置信指派。然后对算法的目标函数进行 循环迭代优化,计算出目标数据最终的全局基本置信指派。最后根据融合结果和所设立的分类规则 即可判断目标的类别属性。通过水声目标实测数据的实验,将新算法与其他几种常用的水声目标识 别算法进行了对比分析,结果表明其能有效提高识别准确率。

Comments: 7 Pages.

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Submission history

[v1] 2018-08-22 02:47:00

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