The dendritic neuron model is a universal approximator

Jingyao Wu, Jiaxin He, Yuki Todo
{"title":"The dendritic neuron model is a universal approximator","authors":"Jingyao Wu, Jiaxin He, Yuki Todo","doi":"10.1109/ICSAI48974.2019.9010178","DOIUrl":null,"url":null,"abstract":"According to the biological composition of neurons, the DNM was invented based on the dendrites of neurons, which can break through the functions that traditional simple neuron model (McCulloch and Pitts, 1943) cannot achieve. While by using traditional single-layer model, the approximation to any continuous function cannot be achieved by a single neuron. In this paper, an accurate mathematical method is used to demonstrate that the DNM can approximate any continuous function which could be achieved with only one neuron.","PeriodicalId":270809,"journal":{"name":"2019 6th International Conference on Systems and Informatics (ICSAI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 6th International Conference on Systems and Informatics (ICSAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAI48974.2019.9010178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

According to the biological composition of neurons, the DNM was invented based on the dendrites of neurons, which can break through the functions that traditional simple neuron model (McCulloch and Pitts, 1943) cannot achieve. While by using traditional single-layer model, the approximation to any continuous function cannot be achieved by a single neuron. In this paper, an accurate mathematical method is used to demonstrate that the DNM can approximate any continuous function which could be achieved with only one neuron.
树突神经元模型是一个通用逼近器
根据神经元的生物组成,DNM是基于神经元的树突而发明的,它可以突破传统的简单神经元模型(McCulloch and Pitts, 1943)无法实现的功能。而传统的单层模型无法通过单个神经元实现对任意连续函数的逼近。本文用一种精确的数学方法证明了DNM可以逼近任何只用一个神经元就能逼近的连续函数。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信