{"title":"视觉运动跟踪系统的数字神经实现","authors":"A. Colla, L. Trogu, R. Zunino","doi":"10.1109/NNSP.1995.514932","DOIUrl":null,"url":null,"abstract":"The paper describes the implementation of neural systems for visual motion tracking on a digital neurocomputing platform, i.e., the NLX420 Neural Processing Slice. The chip architecture and the problem model considered greatly facilitate the implementation task, which involves the fulfilment of critical real-time constraints. Experimental results confirm the approach validity in terms of both speed and prediction accuracy; training adjustment techniques are also examined.","PeriodicalId":403144,"journal":{"name":"Proceedings of 1995 IEEE Workshop on Neural Networks for Signal Processing","volume":"68 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Digital neuroimplementations of visual motion-tracking systems\",\"authors\":\"A. Colla, L. Trogu, R. Zunino\",\"doi\":\"10.1109/NNSP.1995.514932\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper describes the implementation of neural systems for visual motion tracking on a digital neurocomputing platform, i.e., the NLX420 Neural Processing Slice. The chip architecture and the problem model considered greatly facilitate the implementation task, which involves the fulfilment of critical real-time constraints. Experimental results confirm the approach validity in terms of both speed and prediction accuracy; training adjustment techniques are also examined.\",\"PeriodicalId\":403144,\"journal\":{\"name\":\"Proceedings of 1995 IEEE Workshop on Neural Networks for Signal Processing\",\"volume\":\"68 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1995 IEEE Workshop on Neural Networks for Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NNSP.1995.514932\",\"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 1995 IEEE Workshop on Neural Networks for Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NNSP.1995.514932","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Digital neuroimplementations of visual motion-tracking systems
The paper describes the implementation of neural systems for visual motion tracking on a digital neurocomputing platform, i.e., the NLX420 Neural Processing Slice. The chip architecture and the problem model considered greatly facilitate the implementation task, which involves the fulfilment of critical real-time constraints. Experimental results confirm the approach validity in terms of both speed and prediction accuracy; training adjustment techniques are also examined.