{"title":"时变细胞神经网络的图像处理","authors":"N.N. Kamiss Al-Ani, T. Kacprzak","doi":"10.1109/CNNA.1998.685394","DOIUrl":null,"url":null,"abstract":"Properties of cellular neural networks with time-varying gain of cells in the linear part of the transfer function are studied. It is shown that this concept of the CNN dynamics provides new interesting results of image processing tasks which can be used to improve the performance. This aspect is of great importance for the design of VLSI implemented CNN chips. The new properties are documented by the theoretical analysis and computer simulations of three examples.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Image processing using time-varying cellular neural networks\",\"authors\":\"N.N. Kamiss Al-Ani, T. Kacprzak\",\"doi\":\"10.1109/CNNA.1998.685394\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Properties of cellular neural networks with time-varying gain of cells in the linear part of the transfer function are studied. It is shown that this concept of the CNN dynamics provides new interesting results of image processing tasks which can be used to improve the performance. This aspect is of great importance for the design of VLSI implemented CNN chips. The new properties are documented by the theoretical analysis and computer simulations of three examples.\",\"PeriodicalId\":171485,\"journal\":{\"name\":\"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)\",\"volume\":\"145 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"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.1998.685394\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","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.1998.685394","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image processing using time-varying cellular neural networks
Properties of cellular neural networks with time-varying gain of cells in the linear part of the transfer function are studied. It is shown that this concept of the CNN dynamics provides new interesting results of image processing tasks which can be used to improve the performance. This aspect is of great importance for the design of VLSI implemented CNN chips. The new properties are documented by the theoretical analysis and computer simulations of three examples.