{"title":"A new time-multiplexed interconnected architecture with buffering system for multi-chip CNN","authors":"M. Salerno, F. Sargeni, V. Bonaiuto","doi":"10.1109/CNNA.1998.685409","DOIUrl":null,"url":null,"abstract":"Real-time image processing represents an application field where cellular neural networks best show their powerful capabilities because of the full parallel analogue processing feature. For this purpose, the best performances can be carried out with a one-to-one correspondence between the image pixel and the neural cells. Consequently, this leads to the need to build very large CNN chips. In spite of this, these requirements do not agree with the need of the hardware manufacturer to design small chips, which are more reliable from a VLSI implementation point of view. Among the previously proposed solutions to this leading problem, the authors presented a current-mode interconnection-oriented approach able to carry out wide CNN networks making use of small chips. In the paper a technique to improve the interconnection architecture without any lack of functionality is presented.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","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.1998.685409","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Real-time image processing represents an application field where cellular neural networks best show their powerful capabilities because of the full parallel analogue processing feature. For this purpose, the best performances can be carried out with a one-to-one correspondence between the image pixel and the neural cells. Consequently, this leads to the need to build very large CNN chips. In spite of this, these requirements do not agree with the need of the hardware manufacturer to design small chips, which are more reliable from a VLSI implementation point of view. Among the previously proposed solutions to this leading problem, the authors presented a current-mode interconnection-oriented approach able to carry out wide CNN networks making use of small chips. In the paper a technique to improve the interconnection architecture without any lack of functionality is presented.