{"title":"基本哺乳动物视网膜对原型复杂细胞CNN通用机的影响","authors":"D. Bálya, C. Rekeczky, T. Roska","doi":"10.1109/CNNA.2002.1035058","DOIUrl":null,"url":null,"abstract":"The unique possibility for reconstructing the first stage of the visual system on a programmable silicon chip is described. The developed mammalian retinal model can be implemented as an analogic algorithm running on a prototype complex cell cellular neural network processor. It enables the neuro-biological and vision research communities to study the wisdom of biological visual transformations design in real-time. The operating prototype complex-cell CNN-UM processor opens a new world for the engineering as well as the computational neuroscience communities. This paper demonstrates the first steps in this direction. Here we present the decomposition and scaling of one retinal channel as a hardware-level CNN-UM algorithm. The analogic algorithm consists of a series of different complex-cell CNN spatial-temporal dynamics, feasible on the recently fabricated prototype complex cell CNN-UM chip.","PeriodicalId":387716,"journal":{"name":"Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Basic mammalian retinal effects on the prototype complex cell CNN universal machine\",\"authors\":\"D. Bálya, C. Rekeczky, T. Roska\",\"doi\":\"10.1109/CNNA.2002.1035058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The unique possibility for reconstructing the first stage of the visual system on a programmable silicon chip is described. The developed mammalian retinal model can be implemented as an analogic algorithm running on a prototype complex cell cellular neural network processor. It enables the neuro-biological and vision research communities to study the wisdom of biological visual transformations design in real-time. The operating prototype complex-cell CNN-UM processor opens a new world for the engineering as well as the computational neuroscience communities. This paper demonstrates the first steps in this direction. Here we present the decomposition and scaling of one retinal channel as a hardware-level CNN-UM algorithm. The analogic algorithm consists of a series of different complex-cell CNN spatial-temporal dynamics, feasible on the recently fabricated prototype complex cell CNN-UM chip.\",\"PeriodicalId\":387716,\"journal\":{\"name\":\"Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"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.2002.1035058\",\"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.2002.1035058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Basic mammalian retinal effects on the prototype complex cell CNN universal machine
The unique possibility for reconstructing the first stage of the visual system on a programmable silicon chip is described. The developed mammalian retinal model can be implemented as an analogic algorithm running on a prototype complex cell cellular neural network processor. It enables the neuro-biological and vision research communities to study the wisdom of biological visual transformations design in real-time. The operating prototype complex-cell CNN-UM processor opens a new world for the engineering as well as the computational neuroscience communities. This paper demonstrates the first steps in this direction. Here we present the decomposition and scaling of one retinal channel as a hardware-level CNN-UM algorithm. The analogic algorithm consists of a series of different complex-cell CNN spatial-temporal dynamics, feasible on the recently fabricated prototype complex cell CNN-UM chip.