{"title":"高阶随机神经网络的动态特性","authors":"H. Miyajima, Lixin Ma, Hiroyuki Suwa","doi":"10.1109/TAI.1996.560743","DOIUrl":null,"url":null,"abstract":"The authors have previously shown dynamical properties-dynamics of the activities for states-for higher order random neural networks, which use the weighted sum of products of input variables, with the digital state {1-,1} model. The paper describes dynamical properties for higher order random neural networks with the analog state models and the digital state (0,1) model.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Dynamical properties of higher order random neural networks\",\"authors\":\"H. Miyajima, Lixin Ma, Hiroyuki Suwa\",\"doi\":\"10.1109/TAI.1996.560743\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors have previously shown dynamical properties-dynamics of the activities for states-for higher order random neural networks, which use the weighted sum of products of input variables, with the digital state {1-,1} model. The paper describes dynamical properties for higher order random neural networks with the analog state models and the digital state (0,1) model.\",\"PeriodicalId\":209171,\"journal\":{\"name\":\"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence\",\"volume\":\"78 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.1996.560743\",\"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 Eighth IEEE International Conference on Tools with Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1996.560743","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamical properties of higher order random neural networks
The authors have previously shown dynamical properties-dynamics of the activities for states-for higher order random neural networks, which use the weighted sum of products of input variables, with the digital state {1-,1} model. The paper describes dynamical properties for higher order random neural networks with the analog state models and the digital state (0,1) model.