首页 | 本学科首页   官方微博 | 高级检索  
     

基于HHT方法的果蝇鸣声特征提取及分类
引用本文:贾春花,郭敏. 基于HHT方法的果蝇鸣声特征提取及分类[J]. 云南大学学报(自然科学版), 2011, 33(2): 152-157
作者姓名:贾春花  郭敏
作者单位:陕西师范大学计算机科学学院;
基金项目:国家自然科学基金资助项目(10974130)
摘    要: 采用HHT方法对同种内2个不同品系果蝇翅振鸣声进行特征分析,分别提取果蝇翅振鸣声前10阶IMF能量与信号总能量的比值,HH谱图的低频段、中频段、高频段的相对能量值作为特征向量.设计BP神经网络分类器识别不同品系果蝇.实验结果表明,用HHT方法提取特征,神经网络识别不同品系果蝇的方法是可行而有效的,为进一步鉴别果蝇种内关系提供了新的思想和方法.

关 键 词:果蝇鸣声  HHT方法  特征提取  BP神经网络  分类
收稿时间:2010-08-16

Feature extraction and classification of fruit fly's flight sound based on HHT
JIA Chun-hua,GUO Min. Feature extraction and classification of fruit fly's flight sound based on HHT[J]. Journal of Yunnan University(Natural Sciences), 2011, 33(2): 152-157
Authors:JIA Chun-hua  GUO Min
Affiliation:JIA Chun-hua,GUO Min(School of Computer Science,Shaanxi Normal University,Xi'an 710062,China)
Abstract:Using HHT method,the paper analyzed the wing vibration sound of two different strain of fruit flies in the same species.It extracted effective characteristics of fruit fly's wing vibration sound,which contained ratios of first ten IMF and signal total energy,the relative energies of low-frequency stage,middle-frequency stage and high-frequency stage in HH spectrum.Then,the paper designed BP neural network to identify different strain of fruit flies.The experiment result indicated that it was feasible and ef...
Keywords:flight sound of fruit fly  HHT method  feature extraction  BP neural network  classification  
本文献已被 CNKI 等数据库收录!
点击此处可从《云南大学学报(自然科学版)》浏览原始摘要信息
点击此处可从《云南大学学报(自然科学版)》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号