{"title":"Temporal association in symmetric neural networks","authors":"A. Hiroike, T. Omori","doi":"10.1109/IJCNN.1991.170711","DOIUrl":null,"url":null,"abstract":"The authors study temporal association in a stochastic neural network model with symmetric full-connections. A symmetric system is accessible to analysis because of the existence of free-energy. The properties of the model are analytically described by critical temperature of transition between states. The result of the analysis is consistent with Monte Carlo simulations.<<ETX>>","PeriodicalId":211135,"journal":{"name":"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1991-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1991.170711","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The authors study temporal association in a stochastic neural network model with symmetric full-connections. A symmetric system is accessible to analysis because of the existence of free-energy. The properties of the model are analytically described by critical temperature of transition between states. The result of the analysis is consistent with Monte Carlo simulations.<>