{"title":"对神经网络优化技术的几点评述","authors":"N. Attia, J.C. Rose","doi":"10.1109/SECON.1992.202386","DOIUrl":null,"url":null,"abstract":"The authors discuss two optimization techniques for finding the minimum of an objective function while avoiding a saddle point solution. The first is a technique to handle the unconstrained objective function and the second is a technique to handle the constrained optimization problem. The winner-take-all neural network problem and the winner-take-all problem with constraints are considered.<<ETX>>","PeriodicalId":230446,"journal":{"name":"Proceedings IEEE Southeastcon '92","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Some comments on optimization techniques in neural networks\",\"authors\":\"N. Attia, J.C. Rose\",\"doi\":\"10.1109/SECON.1992.202386\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors discuss two optimization techniques for finding the minimum of an objective function while avoiding a saddle point solution. The first is a technique to handle the unconstrained objective function and the second is a technique to handle the constrained optimization problem. The winner-take-all neural network problem and the winner-take-all problem with constraints are considered.<<ETX>>\",\"PeriodicalId\":230446,\"journal\":{\"name\":\"Proceedings IEEE Southeastcon '92\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-04-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE Southeastcon '92\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SECON.1992.202386\",\"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 IEEE Southeastcon '92","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.1992.202386","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Some comments on optimization techniques in neural networks
The authors discuss two optimization techniques for finding the minimum of an objective function while avoiding a saddle point solution. The first is a technique to handle the unconstrained objective function and the second is a technique to handle the constrained optimization problem. The winner-take-all neural network problem and the winner-take-all problem with constraints are considered.<>
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