{"title":"Kohonen高斯混合的量化、分类和密度估计","authors":"R. Gray, K. Perlmutter, R. Olshen","doi":"10.1109/DCC.1998.672132","DOIUrl":null,"url":null,"abstract":"We consider the problem of joint quantization and classification for the example of a simple Gaussian mixture used by Kohonen (1988) to demonstrate the performance of his \"learning vector quantization\" (LVQ). Implicit in the problem is the issue of estimating the underlying densities, which is accomplished by CART/sup TM/ and by an inverse halftoning method.","PeriodicalId":191890,"journal":{"name":"Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Quantization, classification, and density estimation for Kohonen's Gaussian mixture\",\"authors\":\"R. Gray, K. Perlmutter, R. Olshen\",\"doi\":\"10.1109/DCC.1998.672132\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider the problem of joint quantization and classification for the example of a simple Gaussian mixture used by Kohonen (1988) to demonstrate the performance of his \\\"learning vector quantization\\\" (LVQ). Implicit in the problem is the issue of estimating the underlying densities, which is accomplished by CART/sup TM/ and by an inverse halftoning method.\",\"PeriodicalId\":191890,\"journal\":{\"name\":\"Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DCC.1998.672132\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings DCC '98 Data Compression Conference (Cat. No.98TB100225)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.1998.672132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantization, classification, and density estimation for Kohonen's Gaussian mixture
We consider the problem of joint quantization and classification for the example of a simple Gaussian mixture used by Kohonen (1988) to demonstrate the performance of his "learning vector quantization" (LVQ). Implicit in the problem is the issue of estimating the underlying densities, which is accomplished by CART/sup TM/ and by an inverse halftoning method.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
