'Entropy production rate' and 'entropy' for neural networks

Hung-Jen Chang, Kung-Shiuh Huang, Kuan-Tsao Huang
{"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.<>
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
神经网络的“熵产率”和“熵”
导出了神经网络的两个新量——熵产率和熵。在Hopfield神经模型中,Hopfield引入了一个量,能量,能量最小值对应一个问题可能的好的解决方案。结果表明,能量函数与物理学中能量的物理意义不相符;一个更好的物理解释可以通过熵产率和物理学中的熵。这些新量可以进一步推广到神经网络的一般非平衡开放系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
What are the 'carry over effects' in changing from a procedural to a declarative approach? Critical issues in real-time software systems Models to estimate the number of faults still resident in the software after test/debug process Evaluating software development environment quality Structuring large versioned software products
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1