{"title":"基于som的神经网络动态目标识别","authors":"A. Averkin, V. Albu, S. Ulyanov, I. Povidalo","doi":"10.1109/BRICS-CCI-CBIC.2013.12","DOIUrl":null,"url":null,"abstract":"In this article a number of neural networks based on self organizing maps, that can be successfully used for dynamic object identification, is described. The structure and algorithms of learning and operation of such SOM-based neural networks are described in details, also some experimental results is given.","PeriodicalId":306195,"journal":{"name":"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Dynamic Object Identification with SOM-Based Neural Networks\",\"authors\":\"A. Averkin, V. Albu, S. Ulyanov, I. Povidalo\",\"doi\":\"10.1109/BRICS-CCI-CBIC.2013.12\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article a number of neural networks based on self organizing maps, that can be successfully used for dynamic object identification, is described. The structure and algorithms of learning and operation of such SOM-based neural networks are described in details, also some experimental results is given.\",\"PeriodicalId\":306195,\"journal\":{\"name\":\"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BRICS-CCI-CBIC.2013.12\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BRICS-CCI-CBIC.2013.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic Object Identification with SOM-Based Neural Networks
In this article a number of neural networks based on self organizing maps, that can be successfully used for dynamic object identification, is described. The structure and algorithms of learning and operation of such SOM-based neural networks are described in details, also some experimental results is given.
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