{"title":"储层计算:现状?","authors":"A. Goudarzi, C. Teuscher","doi":"10.1145/2967446.2967448","DOIUrl":null,"url":null,"abstract":"Reservoir Computing (RC) is an umbrella term for adaptive computational paradigms that rely on an excitable dynamical system, also called the \"reservoir.\" The paradigms have been shown to be particularly promising for temporal signal processing. RC was also explored as a potential candidate for emerging nanoscale architectures. In this article we reflect on the current state of RC and muse about its future. In particular, we propose a set of open problems that we think need to be addressed in order to make RC more mainstream.","PeriodicalId":281609,"journal":{"name":"Proceedings of the 3rd ACM International Conference on Nanoscale Computing and Communication","volume":"331 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Reservoir Computing: Quo Vadis?\",\"authors\":\"A. Goudarzi, C. Teuscher\",\"doi\":\"10.1145/2967446.2967448\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reservoir Computing (RC) is an umbrella term for adaptive computational paradigms that rely on an excitable dynamical system, also called the \\\"reservoir.\\\" The paradigms have been shown to be particularly promising for temporal signal processing. RC was also explored as a potential candidate for emerging nanoscale architectures. In this article we reflect on the current state of RC and muse about its future. In particular, we propose a set of open problems that we think need to be addressed in order to make RC more mainstream.\",\"PeriodicalId\":281609,\"journal\":{\"name\":\"Proceedings of the 3rd ACM International Conference on Nanoscale Computing and Communication\",\"volume\":\"331 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 3rd ACM International Conference on Nanoscale Computing and Communication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2967446.2967448\",\"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 3rd ACM International Conference on Nanoscale Computing and Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2967446.2967448","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reservoir Computing (RC) is an umbrella term for adaptive computational paradigms that rely on an excitable dynamical system, also called the "reservoir." The paradigms have been shown to be particularly promising for temporal signal processing. RC was also explored as a potential candidate for emerging nanoscale architectures. In this article we reflect on the current state of RC and muse about its future. In particular, we propose a set of open problems that we think need to be addressed in order to make RC more mainstream.