{"title":"基于层次结构随机自动机的带动量反向传播神经网络学习算法研究","authors":"N. Baba, Ken Sato","doi":"10.1109/KES.1998.725945","DOIUrl":null,"url":null,"abstract":"Backpropagation (BP) method with momentum has often been applied to adapt artificial neural networks for various pattern classification problems. However, an important limitation of this method is that its learning performance depends heavily upon the selection of the values of momentum factor and step size. In this paper, it is shown that the hierarchical structure stochastic automata can be used for finding appropriate values of the parameters involved in the BP method with momentum.","PeriodicalId":394492,"journal":{"name":"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A consideration on the learning algorithm of neural network-utilization of the hierarchical structure stochastic automata for the backpropagation method with momentum\",\"authors\":\"N. Baba, Ken Sato\",\"doi\":\"10.1109/KES.1998.725945\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Backpropagation (BP) method with momentum has often been applied to adapt artificial neural networks for various pattern classification problems. However, an important limitation of this method is that its learning performance depends heavily upon the selection of the values of momentum factor and step size. In this paper, it is shown that the hierarchical structure stochastic automata can be used for finding appropriate values of the parameters involved in the BP method with momentum.\",\"PeriodicalId\":394492,\"journal\":{\"name\":\"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)\",\"volume\":\"57 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KES.1998.725945\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KES.1998.725945","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A consideration on the learning algorithm of neural network-utilization of the hierarchical structure stochastic automata for the backpropagation method with momentum
Backpropagation (BP) method with momentum has often been applied to adapt artificial neural networks for various pattern classification problems. However, an important limitation of this method is that its learning performance depends heavily upon the selection of the values of momentum factor and step size. In this paper, it is shown that the hierarchical structure stochastic automata can be used for finding appropriate values of the parameters involved in the BP method with momentum.