{"title":"非迭代Hopfield模型","authors":"A. Edgar, C.Y. Marquez","doi":"10.1109/CERMA.2006.67","DOIUrl":null,"url":null,"abstract":"The Hopfield model has problems in the recall phase, one of them it's the time convergence or non convergence in certain cases. We propose a model that eliminates iteration in Hopfield model. This modification in the recall phase, eliminates the iterations and for consequence takes fewer steps, after them, the recuperation of N patterns learned it's the same or little better than Hopfield model. Finally because iteration is eliminated the recuperation time is reduced too","PeriodicalId":179210,"journal":{"name":"Electronics, Robotics and Automotive Mechanics Conference (CERMA'06)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Non Iterative Hopfield Model\",\"authors\":\"A. Edgar, C.Y. Marquez\",\"doi\":\"10.1109/CERMA.2006.67\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Hopfield model has problems in the recall phase, one of them it's the time convergence or non convergence in certain cases. We propose a model that eliminates iteration in Hopfield model. This modification in the recall phase, eliminates the iterations and for consequence takes fewer steps, after them, the recuperation of N patterns learned it's the same or little better than Hopfield model. Finally because iteration is eliminated the recuperation time is reduced too\",\"PeriodicalId\":179210,\"journal\":{\"name\":\"Electronics, Robotics and Automotive Mechanics Conference (CERMA'06)\",\"volume\":\"151 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronics, Robotics and Automotive Mechanics Conference (CERMA'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CERMA.2006.67\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronics, Robotics and Automotive Mechanics Conference (CERMA'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CERMA.2006.67","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Hopfield model has problems in the recall phase, one of them it's the time convergence or non convergence in certain cases. We propose a model that eliminates iteration in Hopfield model. This modification in the recall phase, eliminates the iterations and for consequence takes fewer steps, after them, the recuperation of N patterns learned it's the same or little better than Hopfield model. Finally because iteration is eliminated the recuperation time is reduced too