Liu Guo-sui, Wang Yunhong, Yang Chunling, Z. Dequan
{"title":"Radar target classification based on radial basis function and modified radial basis function networks","authors":"Liu Guo-sui, Wang Yunhong, Yang Chunling, Z. Dequan","doi":"10.1109/ICR.1996.573808","DOIUrl":null,"url":null,"abstract":"This paper discusses the radial basis function (RBF) neural networks used in the radar target classification. To enhance the classification rate, the structure of the modified radial basis function (MRBF) neural network is proposed. Two kinds of MRBF networks which are called the MRBF1 network and the MRBF2 network are discussed in this paper. From the theory as well as computer simulations, we find that the performance of the MRBF network is superior to the RBF network and the MRBF2 network gets higher classification rate than the MRBF1 network.","PeriodicalId":144063,"journal":{"name":"Proceedings of International Radar Conference","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of International Radar Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICR.1996.573808","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
This paper discusses the radial basis function (RBF) neural networks used in the radar target classification. To enhance the classification rate, the structure of the modified radial basis function (MRBF) neural network is proposed. Two kinds of MRBF networks which are called the MRBF1 network and the MRBF2 network are discussed in this paper. From the theory as well as computer simulations, we find that the performance of the MRBF network is superior to the RBF network and the MRBF2 network gets higher classification rate than the MRBF1 network.