{"title":"问题与策略:内部对称网络的反向传播循环过拟合","authors":"Guanzhong Li","doi":"10.1109/CINC.2009.258","DOIUrl":null,"url":null,"abstract":"Overfitting is an important topic in Neural Network. Internal Symmetry Networks are a new modern Cellular Neural Networks inspired by the phenomenon of internal symmetry in quantum physics. Recurrent Internal Symmetry Networks are just studied very recently. In this paper, overfitting in recurrent cycles of Internal Symmetry Networks is analyzed. Back propagation is trained for an image processing task.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Problem and Strategy: Overfitting in Recurrent Cycles of Internal Symmetry Networks by Back Propagation\",\"authors\":\"Guanzhong Li\",\"doi\":\"10.1109/CINC.2009.258\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Overfitting is an important topic in Neural Network. Internal Symmetry Networks are a new modern Cellular Neural Networks inspired by the phenomenon of internal symmetry in quantum physics. Recurrent Internal Symmetry Networks are just studied very recently. In this paper, overfitting in recurrent cycles of Internal Symmetry Networks is analyzed. Back propagation is trained for an image processing task.\",\"PeriodicalId\":173506,\"journal\":{\"name\":\"2009 International Conference on Computational Intelligence and Natural Computing\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Computational Intelligence and Natural Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CINC.2009.258\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Computational Intelligence and Natural Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINC.2009.258","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Problem and Strategy: Overfitting in Recurrent Cycles of Internal Symmetry Networks by Back Propagation
Overfitting is an important topic in Neural Network. Internal Symmetry Networks are a new modern Cellular Neural Networks inspired by the phenomenon of internal symmetry in quantum physics. Recurrent Internal Symmetry Networks are just studied very recently. In this paper, overfitting in recurrent cycles of Internal Symmetry Networks is analyzed. Back propagation is trained for an image processing task.