MIMO采样神经网络的软件实现

IF 1.9 4区 计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING SoftwareX Pub Date : 2025-02-01 Epub Date: 2024-12-18 DOI:10.1016/j.softx.2024.102017
Lingyan Wu , Gang Cai
{"title":"MIMO采样神经网络的软件实现","authors":"Lingyan Wu ,&nbsp;Gang Cai","doi":"10.1016/j.softx.2024.102017","DOIUrl":null,"url":null,"abstract":"<div><div>This is a software tool that provides the program implementation for MIMO Sampling Neural Network (SNN) and Wide Learning. MIMO SNN is a novel neural network that combines SISO SNN with SLFNs structure to fill the gap of SISO SNN and trains the neurons with trainable activation functions in SISO SNN instead of weights. Wide Learning is an extended algorithm of MIMO SNN and trains the network by adding and updating the new neurons. The experimental results show that the algorithm has good accuracy and convergence features. The software is beneficial to expand the application prospect of the algorithm in instant training, self-growth, big data, and other aspects.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"29 ","pages":"Article 102017"},"PeriodicalIF":1.9000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MIMOSNN: Software implementation for MIMO sampling neural network\",\"authors\":\"Lingyan Wu ,&nbsp;Gang Cai\",\"doi\":\"10.1016/j.softx.2024.102017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This is a software tool that provides the program implementation for MIMO Sampling Neural Network (SNN) and Wide Learning. MIMO SNN is a novel neural network that combines SISO SNN with SLFNs structure to fill the gap of SISO SNN and trains the neurons with trainable activation functions in SISO SNN instead of weights. Wide Learning is an extended algorithm of MIMO SNN and trains the network by adding and updating the new neurons. The experimental results show that the algorithm has good accuracy and convergence features. The software is beneficial to expand the application prospect of the algorithm in instant training, self-growth, big data, and other aspects.</div></div>\",\"PeriodicalId\":21905,\"journal\":{\"name\":\"SoftwareX\",\"volume\":\"29 \",\"pages\":\"Article 102017\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SoftwareX\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S235271102400387X\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/12/18 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SoftwareX","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S235271102400387X","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/18 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0

摘要

这是一个软件工具,提供了MIMO采样神经网络(SNN)和广泛学习的程序实现。MIMO SNN是一种新型的神经网络,它将SISO SNN与SLFNs结构相结合,填补了SISO SNN的空白,并在SISO SNN中训练具有可训练激活函数的神经元,而不是权重。Wide Learning是MIMO SNN的一种扩展算法,通过增加和更新新的神经元来训练网络。实验结果表明,该算法具有良好的精度和收敛性。该软件有利于拓展算法在即时训练、自我成长、大数据等方面的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
MIMOSNN: Software implementation for MIMO sampling neural network
This is a software tool that provides the program implementation for MIMO Sampling Neural Network (SNN) and Wide Learning. MIMO SNN is a novel neural network that combines SISO SNN with SLFNs structure to fill the gap of SISO SNN and trains the neurons with trainable activation functions in SISO SNN instead of weights. Wide Learning is an extended algorithm of MIMO SNN and trains the network by adding and updating the new neurons. The experimental results show that the algorithm has good accuracy and convergence features. The software is beneficial to expand the application prospect of the algorithm in instant training, self-growth, big data, and other aspects.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
SoftwareX
SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
5.50
自引率
2.90%
发文量
184
审稿时长
9 weeks
期刊介绍: SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.
期刊最新文献
TRNSYS-AgentControl: A Python-based framework for agent-driven supervisory control workflows in TRNSYS A symplectic integrator for a native relativistic orbitography software InTrade: A Python package for MRIO-based value-added and structural gravity analysis FaceTrackingKit: Simplifying background face tracking for iOS research apps rdf12conv: A lightweight RDF 1.2 converter for N-Triples, N-Quads, Turtle, and TriG
×
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