{"title":"mL-CNN: m组分系统中反应扩散过程的CNN模型","authors":"A. Selikhov","doi":"10.1109/CNNA.2002.1035041","DOIUrl":null,"url":null,"abstract":"A mL-CNN is presented in this paper as a generalization of CNN models of reaction-diffusion processes in nonlinear media with m components. Main properties of the model are considered in accordance with imaginations of the process \"mechanisms\". Two particular CNN models, an autonomous 2L-CNN and a 2L-CNN with external inputs, are presented as examples of special cases of the mL-CNN. Emergence of some complex phenomena in such particular models are also shown.","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":"2002-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"mL-CNN: a CNN model for reaction-diffusion processes in m-component systems\",\"authors\":\"A. Selikhov\",\"doi\":\"10.1109/CNNA.2002.1035041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A mL-CNN is presented in this paper as a generalization of CNN models of reaction-diffusion processes in nonlinear media with m components. Main properties of the model are considered in accordance with imaginations of the process \\\"mechanisms\\\". Two particular CNN models, an autonomous 2L-CNN and a 2L-CNN with external inputs, are presented as examples of special cases of the mL-CNN. Emergence of some complex phenomena in such particular models are also shown.\",\"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\":\"2002-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"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.2002.1035041\",\"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 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CNNA.2002.1035041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
mL-CNN: a CNN model for reaction-diffusion processes in m-component systems
A mL-CNN is presented in this paper as a generalization of CNN models of reaction-diffusion processes in nonlinear media with m components. Main properties of the model are considered in accordance with imaginations of the process "mechanisms". Two particular CNN models, an autonomous 2L-CNN and a 2L-CNN with external inputs, are presented as examples of special cases of the mL-CNN. Emergence of some complex phenomena in such particular models are also shown.
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