鲁棒性抗S.E.U.的一种人工神经网络空间应用

Proceedings of the Third European Conference on Radiation and its Effects on Components and Systems Pub Date : 1995-09-18 DOI:10.1109/RADECS.1995.509817

A. Assoum, M. E. Radi, Raoul Velazco, F. Elie, R. Ecoffet

{"title":"鲁棒性抗S.E.U.的一种人工神经网络空间应用","authors":"A. Assoum, M. E. Radi, Raoul Velazco, F. Elie, R. Ecoffet","doi":"10.1109/RADECS.1995.509817","DOIUrl":null,"url":null,"abstract":"We study the sensitivity of Artificial Neural Networks (ANN) to Single Event Upsets (SEU). A neural network designed to detect electronic and protonic whistlers has been implemented using a dedicated VLSI circuit: the LNeuro neural processor. Results of both SEU software simulations and heavy ion tests point out the fault tolerance properties of ANN hardware implementations.","PeriodicalId":310087,"journal":{"name":"Proceedings of the Third European Conference on Radiation and its Effects on Components and Systems","volume":"230 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Robustness against S.E.U. of an artificial neural network space application\",\"authors\":\"A. Assoum, M. E. Radi, Raoul Velazco, F. Elie, R. Ecoffet\",\"doi\":\"10.1109/RADECS.1995.509817\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We study the sensitivity of Artificial Neural Networks (ANN) to Single Event Upsets (SEU). A neural network designed to detect electronic and protonic whistlers has been implemented using a dedicated VLSI circuit: the LNeuro neural processor. Results of both SEU software simulations and heavy ion tests point out the fault tolerance properties of ANN hardware implementations.\",\"PeriodicalId\":310087,\"journal\":{\"name\":\"Proceedings of the Third European Conference on Radiation and its Effects on Components and Systems\",\"volume\":\"230 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Third European Conference on Radiation and its Effects on Components and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADECS.1995.509817\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Third European Conference on Radiation and its Effects on Components and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADECS.1995.509817","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 13

摘要

研究人工神经网络(ANN)对单事件扰动(SEU)的敏感性。一个用于探测电子和质子哨子的神经网络已经使用专用的VLSI电路:LNeuro神经处理器实现。SEU软件仿真和重离子测试结果表明了人工神经网络硬件实现的容错性能。

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

Robustness against S.E.U. of an artificial neural network space application

We study the sensitivity of Artificial Neural Networks (ANN) to Single Event Upsets (SEU). A neural network designed to detect electronic and protonic whistlers has been implemented using a dedicated VLSI circuit: the LNeuro neural processor. Results of both SEU software simulations and heavy ion tests point out the fault tolerance properties of ANN hardware implementations.

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

Proceedings of the Third European Conference on Radiation and its Effects on Components and Systems

自引率

0.00%

发文量