{"title":"一种有效的目标分类方法","authors":"Yanning Zhang, L. Jiao, Hu Songhua","doi":"10.1109/ICOSP.1998.770828","DOIUrl":null,"url":null,"abstract":"The People's Republic of China's fishery and offshore petroleum development industries have been in urgent need of a classifier of noise signals. In this paper, a local adaptive wavelet neural network is proposed, and an efficient engineering classifier based on the local adaptive wavelet neural network is designed and applied to classifying actual ship noises. The classification experiment results are encouraging, which shows that the classifier above is an efficient engineering classifier for actual ship noises.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An efficient method of target classification\",\"authors\":\"Yanning Zhang, L. Jiao, Hu Songhua\",\"doi\":\"10.1109/ICOSP.1998.770828\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The People's Republic of China's fishery and offshore petroleum development industries have been in urgent need of a classifier of noise signals. In this paper, a local adaptive wavelet neural network is proposed, and an efficient engineering classifier based on the local adaptive wavelet neural network is designed and applied to classifying actual ship noises. The classification experiment results are encouraging, which shows that the classifier above is an efficient engineering classifier for actual ship noises.\",\"PeriodicalId\":145700,\"journal\":{\"name\":\"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOSP.1998.770828\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSP.1998.770828","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The People's Republic of China's fishery and offshore petroleum development industries have been in urgent need of a classifier of noise signals. In this paper, a local adaptive wavelet neural network is proposed, and an efficient engineering classifier based on the local adaptive wavelet neural network is designed and applied to classifying actual ship noises. The classification experiment results are encouraging, which shows that the classifier above is an efficient engineering classifier for actual ship noises.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
