M. Cutajar, E. Gatt, J. Micallef, I. Grech, O. Casha
{"title":"自组织地图的数字硬件实现","authors":"M. Cutajar, E. Gatt, J. Micallef, I. Grech, O. Casha","doi":"10.1109/MELCON.2010.5476361","DOIUrl":null,"url":null,"abstract":"In this paper a digital hardware implementation of the Self-Organising Maps (SOMs) for the application of handwritten digit recognition is presented. Two methods were implemented: Euclidean and Manhattan method. The highest recognition rate for both methods was calculated through three testing techniques. The highest recognition rates obtained are 71.267% and 63.667% for the Euclidean and the Manhattan methods respectively. Both methods were implemented on the Xilinx Spartan-3 200K gates (XC3S200) to compare their speed performance and area consumed.","PeriodicalId":256057,"journal":{"name":"Melecon 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Digital hardware implementation of Self-Organising Maps\",\"authors\":\"M. Cutajar, E. Gatt, J. Micallef, I. Grech, O. Casha\",\"doi\":\"10.1109/MELCON.2010.5476361\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a digital hardware implementation of the Self-Organising Maps (SOMs) for the application of handwritten digit recognition is presented. Two methods were implemented: Euclidean and Manhattan method. The highest recognition rate for both methods was calculated through three testing techniques. The highest recognition rates obtained are 71.267% and 63.667% for the Euclidean and the Manhattan methods respectively. Both methods were implemented on the Xilinx Spartan-3 200K gates (XC3S200) to compare their speed performance and area consumed.\",\"PeriodicalId\":256057,\"journal\":{\"name\":\"Melecon 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference\",\"volume\":\"73 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Melecon 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MELCON.2010.5476361\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Melecon 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MELCON.2010.5476361","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Digital hardware implementation of Self-Organising Maps
In this paper a digital hardware implementation of the Self-Organising Maps (SOMs) for the application of handwritten digit recognition is presented. Two methods were implemented: Euclidean and Manhattan method. The highest recognition rate for both methods was calculated through three testing techniques. The highest recognition rates obtained are 71.267% and 63.667% for the Euclidean and the Manhattan methods respectively. Both methods were implemented on the Xilinx Spartan-3 200K gates (XC3S200) to compare their speed performance and area consumed.