{"title":"用序列泄漏积分器映射分析连续时间序列","authors":"C. Privitera, P. Morasso","doi":"10.1109/ICNN.1994.374733","DOIUrl":null,"url":null,"abstract":"The problem to detect and recognize the occurrence of specific events in a continually evolving environment, is particularly important in many fields, starting from motor planning. In this paper, the authors propose a two-dimensional map, where the processing elements correspond to specific instances of leaky integrators whose parameters (or tops) are learned in a self-organizing manner: in this way the map becomes a topologic representation of temporal sequences whose presence in a continuous temporal data flow is detectable by means of the activation level of the corresponding neurons.<<ETX>>","PeriodicalId":209128,"journal":{"name":"Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"The analysis of continuous temporal sequences by a map of sequential leaky integrators\",\"authors\":\"C. Privitera, P. Morasso\",\"doi\":\"10.1109/ICNN.1994.374733\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem to detect and recognize the occurrence of specific events in a continually evolving environment, is particularly important in many fields, starting from motor planning. In this paper, the authors propose a two-dimensional map, where the processing elements correspond to specific instances of leaky integrators whose parameters (or tops) are learned in a self-organizing manner: in this way the map becomes a topologic representation of temporal sequences whose presence in a continuous temporal data flow is detectable by means of the activation level of the corresponding neurons.<<ETX>>\",\"PeriodicalId\":209128,\"journal\":{\"name\":\"Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"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.1994.374733\",\"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.1994.374733","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The analysis of continuous temporal sequences by a map of sequential leaky integrators
The problem to detect and recognize the occurrence of specific events in a continually evolving environment, is particularly important in many fields, starting from motor planning. In this paper, the authors propose a two-dimensional map, where the processing elements correspond to specific instances of leaky integrators whose parameters (or tops) are learned in a self-organizing manner: in this way the map becomes a topologic representation of temporal sequences whose presence in a continuous temporal data flow is detectable by means of the activation level of the corresponding neurons.<>