{"title":"生物信号工程集成智能分类引擎(I2CE)","authors":"A. Kastania, M. P. Bekakos","doi":"10.1142/9789812778086_0012","DOIUrl":null,"url":null,"abstract":"Speed of execution is an important issue in applying an Artificial Neural Network (ANN) to any real-time problem. Adaptive Logic Networks (ALNs) are a type of ANNs, which allow the solution of pattern classification problems at very high speed based on traversal of a binary decision tree architecture. Herein, various ALN architectures were built and evaluated based on the relational approach for ALNs. The outcome was the development of an integrated intelligent classification engine (I2CE) for biosignal engineering purposes.","PeriodicalId":212567,"journal":{"name":"Neural Parallel Sci. Comput.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated intelligent classification engine (I2CE) for biosignal engineering\",\"authors\":\"A. Kastania, M. P. Bekakos\",\"doi\":\"10.1142/9789812778086_0012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Speed of execution is an important issue in applying an Artificial Neural Network (ANN) to any real-time problem. Adaptive Logic Networks (ALNs) are a type of ANNs, which allow the solution of pattern classification problems at very high speed based on traversal of a binary decision tree architecture. Herein, various ALN architectures were built and evaluated based on the relational approach for ALNs. The outcome was the development of an integrated intelligent classification engine (I2CE) for biosignal engineering purposes.\",\"PeriodicalId\":212567,\"journal\":{\"name\":\"Neural Parallel Sci. Comput.\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neural Parallel Sci. Comput.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/9789812778086_0012\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Parallel Sci. Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/9789812778086_0012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Integrated intelligent classification engine (I2CE) for biosignal engineering
Speed of execution is an important issue in applying an Artificial Neural Network (ANN) to any real-time problem. Adaptive Logic Networks (ALNs) are a type of ANNs, which allow the solution of pattern classification problems at very high speed based on traversal of a binary decision tree architecture. Herein, various ALN architectures were built and evaluated based on the relational approach for ALNs. The outcome was the development of an integrated intelligent classification engine (I2CE) for biosignal engineering purposes.