离散时间细胞神经网络的全局渐近稳定性

1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI:10.1109/CNNA.1998.685329

S. Arik, A. Kılınç, F. Acar Savaci

{"title":"离散时间细胞神经网络的全局渐近稳定性","authors":"S. Arik, A. Kılınç, F. Acar Savaci","doi":"10.1109/CNNA.1998.685329","DOIUrl":null,"url":null,"abstract":"This paper presents two sufficient conditions for global stability of discrete-time cellular neural networks (DTCNNs). It is shown that if the first or second norm of the feedback matrix is smaller than one, then a DTCNN converges to a unique and globally asymptotically stable equilibrium point for every external input.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Global asymptotic stability of discrete-time cellular neural networks\",\"authors\":\"S. Arik, A. Kılınç, F. Acar Savaci\",\"doi\":\"10.1109/CNNA.1998.685329\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents two sufficient conditions for global stability of discrete-time cellular neural networks (DTCNNs). It is shown that if the first or second norm of the feedback matrix is smaller than one, then a DTCNN converges to a unique and globally asymptotically stable equilibrium point for every external input.\",\"PeriodicalId\":171485,\"journal\":{\"name\":\"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)\",\"volume\":\"145 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CNNA.1998.685329\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CNNA.1998.685329","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 4

摘要

本文给出了离散时间细胞神经网络(DTCNNs)全局稳定的两个充分条件。结果表明，如果反馈矩阵的第一范数或第二范数小于1，则对于每个外部输入，DTCNN收敛到唯一且全局渐近稳定的平衡点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Global asymptotic stability of discrete-time cellular neural networks

This paper presents two sufficient conditions for global stability of discrete-time cellular neural networks (DTCNNs). It is shown that if the first or second norm of the feedback matrix is smaller than one, then a DTCNN converges to a unique and globally asymptotically stable equilibrium point for every external input.

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

1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)

自引率

0.00%

发文量