{"title":"特征可判别性改进了分类方法","authors":"Xiangdong Jiang","doi":"10.1109/COA.2016.7535628","DOIUrl":null,"url":null,"abstract":"To improve the weak discriminability of the feature vector for underwater acoustic classification, a new methods of feature differentiation optimization was proposed in this paper. By mapping the feature vectors to transform space, we can enhance the differentiation. Data processing results proved the advantage of higher classification correct ratio and feature vector dimension reduction of the promoted method.","PeriodicalId":155481,"journal":{"name":"2016 IEEE/OES China Ocean Acoustics (COA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Feature discriminability improve methods for classification\",\"authors\":\"Xiangdong Jiang\",\"doi\":\"10.1109/COA.2016.7535628\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To improve the weak discriminability of the feature vector for underwater acoustic classification, a new methods of feature differentiation optimization was proposed in this paper. By mapping the feature vectors to transform space, we can enhance the differentiation. Data processing results proved the advantage of higher classification correct ratio and feature vector dimension reduction of the promoted method.\",\"PeriodicalId\":155481,\"journal\":{\"name\":\"2016 IEEE/OES China Ocean Acoustics (COA)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE/OES China Ocean Acoustics (COA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COA.2016.7535628\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/OES China Ocean Acoustics (COA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COA.2016.7535628","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Feature discriminability improve methods for classification
To improve the weak discriminability of the feature vector for underwater acoustic classification, a new methods of feature differentiation optimization was proposed in this paper. By mapping the feature vectors to transform space, we can enhance the differentiation. Data processing results proved the advantage of higher classification correct ratio and feature vector dimension reduction of the promoted method.