{"title":"'Entropy production rate' and 'entropy' for neural networks","authors":"Hung-Jen Chang, Kung-Shiuh Huang, Kuan-Tsao Huang","doi":"10.1109/CMPSAC.1989.65162","DOIUrl":null,"url":null,"abstract":"Two new quantities for neural networks, entropy production rate and entropy, are derived. In the Hopfield neural model, Hopfield introduced a quantity, energy, and the energy minimum corresponds to a possible good solution to a problem. It is shown that the energy function does not match the physical meaning of energy in physics; a better physical interpretation can go through entropy production rate and entropy in physics. These new quantities can be further extended to general nonequilibrium open systems for neural networks.<<ETX>>","PeriodicalId":339677,"journal":{"name":"[1989] Proceedings of the Thirteenth Annual International Computer Software & Applications Conference","volume":"205 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1989] Proceedings of the Thirteenth Annual International Computer Software & Applications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CMPSAC.1989.65162","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
Two new quantities for neural networks, entropy production rate and entropy, are derived. In the Hopfield neural model, Hopfield introduced a quantity, energy, and the energy minimum corresponds to a possible good solution to a problem. It is shown that the energy function does not match the physical meaning of energy in physics; a better physical interpretation can go through entropy production rate and entropy in physics. These new quantities can be further extended to general nonequilibrium open systems for neural networks.<>