Chung-Yu Wu, Chieh-Yu Hsieh, Sheng-Hao Chen, B. C. Hsieh, Cheng-Ruei Chen
{"title":"Non-saturated binary image learning and recognition using the ratio-memory cellular neural network (RMCNN)","authors":"Chung-Yu Wu, Chieh-Yu Hsieh, Sheng-Hao Chen, B. C. Hsieh, Cheng-Ruei Chen","doi":"10.1109/CNNA.2002.1035104","DOIUrl":null,"url":null,"abstract":"In this paper, cellular neural network with ratio memory is proposed for non-saturated binary image processing. The Hebbien leaming lule will be used to leam the weight oftemplate A. The RMCNN system can recognize one non-saNmted binary image and remove most ofthe noise added to the image pattem during the recognition period. The behavior of recognizing non-saturated binary images will be proved by mathematics equations. The effect will be simulated by Matlab sothare. With the method for non-SaNrated binarylmage processing, this theory can be easily implemented in hardware.","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":"2002-07-24","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.2002.1035104","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 paper, cellular neural network with ratio memory is proposed for non-saturated binary image processing. The Hebbien leaming lule will be used to leam the weight oftemplate A. The RMCNN system can recognize one non-saNmted binary image and remove most ofthe noise added to the image pattem during the recognition period. The behavior of recognizing non-saturated binary images will be proved by mathematics equations. The effect will be simulated by Matlab sothare. With the method for non-SaNrated binarylmage processing, this theory can be easily implemented in hardware.