删除或更新信息，请邮件至freekaoyan#163.com(#换成@)

基于改进支持向量机的水声目标-杂波不平衡分类研究

本站小编 Free考研考试/2022-01-02
-->
关鑫,李然威,胡鹏,冯金鹿,何荣钦.基于改进支持向量机的水声目标-杂波不平衡分类研究[J].,2021,40(5):715-722
基于改进支持向量机的水声目标-杂波不平衡分类研究
Research on imbalanced classification of underwater acoustic target-clutter based on improved support vector machine
投稿时间：2020-10-09修订日期：2021-09-02
中文摘要:
针对水声目标-杂波数据集在有限样本下的类不平衡特性,导致代价敏感支持向量机难以逼近贝叶斯最优决策的问题,本文提出了一种基于能量统计(Energy statistics)方法的支持向量机(En-SVM)。该算法通过度量原始数据空间与有限样本空间特征函数之间的加权平方距离,量化少数类样本不完全采样过程中的信息损失,来补偿再生核希尔伯特空间中机器学习算法所需的少数类分类信息,增加少数类样本对决策的影响力。实验结果表明,En-SVM能够在保持高检测概率的同时获得较低虚警概率,即通过分类可以排除大量的杂波,性能优于标准支持向量机和代价敏感支持向量机,能够有效处理水声不平衡数据的分类问题,实现主动声呐信号处理中的杂波抑制。
英文摘要:
This paper mainly proposed a novel algorithm En-SVM based on energy statistics method for the imbalance characteristics of acoustic target-clutter data sets resulted in cost sensitive support vector machines didn’t approach Bayesian optimal decision in limited samples. This algorithm measured the weighted square distance between the original data space and the feature function of the limited sample space, quantifies the information loss in the incomplete sampling process of a few samples, so as to compensate for the minority class classification information required by the machine learning algorithm in the reproducing kernel Hilbert space, and increased the influence of the minority class samples on the decision-making. The experimental results show that the proposed algorithm can obtain a lower false alarm probability while maintaining a high detection probability, which means that a large amount of clutter can be eliminated by classification, and the performance is better than that of standard SVM and CS-SVM, which can effectively deal with the classification problem of underwater acoustic unbalanced data and realize clutter suppression of active sonar signal processing.
DOI：10.11684/j.issn.1000-310X.2021.05.009
中文关键词:目标杂波分类不平衡分类支持向量机能量统计
英文关键词:target-clutter classificationimbalance classificationsupport vector machineenergy statistics
基金项目:
作者单位E-mail
关鑫中国船舶第七一五研究所 杭州 31002315091096899@163.com
李然威中国船舶第七一五研究所 杭州 310023lirw501@sina.com
胡鹏中国船舶第七一五研究所
冯金鹿中国船舶第七一五研究所 杭州 310023
何荣钦中国船舶第七一五研究所
摘要点击次数:277
全文下载次数:222
查看全文查看/发表评论下载PDF阅读器
相关附件：附件1保密审查证明附件2成果说明修改说明1修改说明1修改说明2修改说明2附件1
关闭








PDF全文下载地址:

http://yysx.cnjournals.cn/ch/reader/create_pdf.aspx?file_no=20205&flag=1&journal_id=yysx&year_id=2021
相关话题/研究所 空间 数据 中文 统计

Free考研考试FreeKaoYan.Com
欢迎来到Free考研考试，"为实现人生的Free而奋斗"

© 2020 FreeKaoYan! . All rights reserved.