Teaching CNN and learning by using CNN

P. Arena, A. Basile, M. Bucolo, L. Fortuna
{"title":"Teaching CNN and learning by using CNN","authors":"P. Arena, A. Basile, M. Bucolo, L. Fortuna","doi":"10.1109/CNNA.2002.1035100","DOIUrl":null,"url":null,"abstract":"In this communication we remark our experience in teaching CNN technologies at the Universita degli Studi di Catania in the course of Adaptive Systems. The main result regards the possibility of using the CNN subject to introduce further topics in circuits and dynamical systems. The students reached high level skills in the related field. Moreover they have developed personalized simulation tools that used to make more experiments confirming that CNN are really the real paradigm for complexity.","PeriodicalId":387716,"journal":{"name":"Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2002-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CNNA.2002.1035100","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

In this communication we remark our experience in teaching CNN technologies at the Universita degli Studi di Catania in the course of Adaptive Systems. The main result regards the possibility of using the CNN subject to introduce further topics in circuits and dynamical systems. The students reached high level skills in the related field. Moreover they have developed personalized simulation tools that used to make more experiments confirming that CNN are really the real paradigm for complexity.
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
教CNN,用CNN学
在这次交流中,我们谈到了我们在卡塔尼亚大学自适应系统课程中教授CNN技术的经验。主要结果考虑了使用CNN主题在电路和动力系统中引入进一步主题的可能性。学生们在相关领域达到了高水平的技能。此外,他们还开发了个性化的仿真工具,用于进行更多的实验,以证实CNN确实是复杂性的真正范例。
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
Non-saturated binary image learning and recognition using the ratio-memory cellular neural network (RMCNN) Analogic preprocessing and segmentation algorithms for off-line handwriting recognition Statistical error modeling of CNN-UM architectures: the binary case Realization of couplings in a polynomial type mixed-mode CNN Configurable multi-layer CNN-UM emulator on FPGA
×
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:481959085
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