{"title":"FPGA implementation of MFNN for image registration","authors":"D. Gharpure, M. Puranik","doi":"10.1109/FPT.2002.1188712","DOIUrl":null,"url":null,"abstract":"The multilayer feedforward neural network (MFNN) is modified to simplify hardware realization and at the same time retain the accuracy of detection. The results obtained have been found to be comparable to the software simulation algorithm which is used as a test base. The MFNN implementation involves low hardware complexity, good noise immunity and fast circuitry.","PeriodicalId":355740,"journal":{"name":"2002 IEEE International Conference on Field-Programmable Technology, 2002. (FPT). Proceedings.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2002 IEEE International Conference on Field-Programmable Technology, 2002. (FPT). Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPT.2002.1188712","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
The multilayer feedforward neural network (MFNN) is modified to simplify hardware realization and at the same time retain the accuracy of detection. The results obtained have been found to be comparable to the software simulation algorithm which is used as a test base. The MFNN implementation involves low hardware complexity, good noise immunity and fast circuitry.