{"title":"可重入脉冲耦合神经网络","authors":"F. Allen, H. Caulfield","doi":"10.1109/ICNN.1994.374370","DOIUrl":null,"url":null,"abstract":"The PCNN developed by Johnson (1993) are syntactic pattern transformers. Hence their outputs are quite similar over a wide variety of \"distortions\". We show that we can convert a PCNN into an attractor system which, away from boundaries, produces point attractor icons which are ideal inputs to statistical pattern processors.<<ETX>>","PeriodicalId":209128,"journal":{"name":"Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reentrant pulse coupled neural networks (PCNNs)\",\"authors\":\"F. Allen, H. Caulfield\",\"doi\":\"10.1109/ICNN.1994.374370\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The PCNN developed by Johnson (1993) are syntactic pattern transformers. Hence their outputs are quite similar over a wide variety of \\\"distortions\\\". We show that we can convert a PCNN into an attractor system which, away from boundaries, produces point attractor icons which are ideal inputs to statistical pattern processors.<<ETX>>\",\"PeriodicalId\":209128,\"journal\":{\"name\":\"Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNN.1994.374370\",\"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 1994 IEEE International Conference on Neural Networks (ICNN'94)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNN.1994.374370","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The PCNN developed by Johnson (1993) are syntactic pattern transformers. Hence their outputs are quite similar over a wide variety of "distortions". We show that we can convert a PCNN into an attractor system which, away from boundaries, produces point attractor icons which are ideal inputs to statistical pattern processors.<>