人工神经网络中的奇异摄动和时间尺度

[1991] Proceedings of the 30th IEEE Conference on Decision and Control Pub Date : 1991-12-11 DOI:10.1109/CDC.1991.261077

K. L. Moore, D. Naidu

{"title":"人工神经网络中的奇异摄动和时间尺度","authors":"K. L. Moore, D. Naidu","doi":"10.1109/CDC.1991.261077","DOIUrl":null,"url":null,"abstract":"The learning and computing processes in a recursive neural network of the Hopfield type are identified as slow and fast phenomena. The corresponding dynamical equations are cast to fit into the framework of the theory of singular perturbations and time scales. The issues of degeneration and asymptotic expansions arising in obtaining approximate solutions are addressed.<<ETX>>","PeriodicalId":344553,"journal":{"name":"[1991] Proceedings of the 30th IEEE Conference on Decision and Control","volume":"182 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Singular perturbations and time scales in artificial neural networks\",\"authors\":\"K. L. Moore, D. Naidu\",\"doi\":\"10.1109/CDC.1991.261077\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The learning and computing processes in a recursive neural network of the Hopfield type are identified as slow and fast phenomena. The corresponding dynamical equations are cast to fit into the framework of the theory of singular perturbations and time scales. The issues of degeneration and asymptotic expansions arising in obtaining approximate solutions are addressed.<<ETX>>\",\"PeriodicalId\":344553,\"journal\":{\"name\":\"[1991] Proceedings of the 30th IEEE Conference on Decision and Control\",\"volume\":\"182 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1991] Proceedings of the 30th IEEE Conference on Decision and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.1991.261077\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991] Proceedings of the 30th IEEE Conference on Decision and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1991.261077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

在Hopfield型递归神经网络中，学习和计算过程分为慢现象和快现象。将相应的动力学方程转换成奇异摄动和时间尺度理论的框架。讨论了在求近似解时出现的退化和渐近展开问题。

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

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Singular perturbations and time scales in artificial neural networks

The learning and computing processes in a recursive neural network of the Hopfield type are identified as slow and fast phenomena. The corresponding dynamical equations are cast to fit into the framework of the theory of singular perturbations and time scales. The issues of degeneration and asymptotic expansions arising in obtaining approximate solutions are addressed.<>

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

[1991] Proceedings of the 30th IEEE Conference on Decision and Control

自引率

0.00%

发文量