{"title":"An FPGA-based on-line neural system in photon counting intensified imagers for space applications","authors":"M. Alderighi, S. D'Angelo, G. Sechi, F. d'Ovidio","doi":"10.1109/ICAPP.1997.651530","DOIUrl":null,"url":null,"abstract":"A computational system based on a synchronous feedback neural network for the online event processing of a photon counting intensified CCD detector is presented. The hardware prototype, implemented by means of FPGA technology, consists of 5/spl times/5 and is able to identify photon events against spurious and/or noise events. It shows a high level of flexibility, which is essential in the characterization phase of the detector. It allows to implement different kinds of neurons, having different output functions and internal architectures, and to run actual, as well as virtual, networks of neurons.","PeriodicalId":325978,"journal":{"name":"Proceedings of 3rd International Conference on Algorithms and Architectures for Parallel Processing","volume":"163 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd International Conference on Algorithms and Architectures for Parallel Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAPP.1997.651530","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A computational system based on a synchronous feedback neural network for the online event processing of a photon counting intensified CCD detector is presented. The hardware prototype, implemented by means of FPGA technology, consists of 5/spl times/5 and is able to identify photon events against spurious and/or noise events. It shows a high level of flexibility, which is essential in the characterization phase of the detector. It allows to implement different kinds of neurons, having different output functions and internal architectures, and to run actual, as well as virtual, networks of neurons.
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