{"title":"PLN网络中学习算法的复杂性","authors":"B. Zhang, L. Zhang, H. Zhang","doi":"10.1109/IJCNN.1991.170347","DOIUrl":null,"url":null,"abstract":"The complexity of the learning algorithm in the PLN (probabilistic logic neuron) network is investigated by using Markov chain theory. A computer simulation of a parity-checking problem has been implemented on a SUN-3 workstation using the C language. The results are given to show the correctness of the theoretical analysis.<<ETX>>","PeriodicalId":211135,"journal":{"name":"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1991-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The complexity of learning algorithm in PLN network\",\"authors\":\"B. Zhang, L. Zhang, H. Zhang\",\"doi\":\"10.1109/IJCNN.1991.170347\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The complexity of the learning algorithm in the PLN (probabilistic logic neuron) network is investigated by using Markov chain theory. A computer simulation of a parity-checking problem has been implemented on a SUN-3 workstation using the C language. The results are given to show the correctness of the theoretical analysis.<<ETX>>\",\"PeriodicalId\":211135,\"journal\":{\"name\":\"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings] 1991 IEEE International Joint Conference on Neural Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.1991.170347\",\"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] 1991 IEEE International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1991.170347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The complexity of learning algorithm in PLN network
The complexity of the learning algorithm in the PLN (probabilistic logic neuron) network is investigated by using Markov chain theory. A computer simulation of a parity-checking problem has been implemented on a SUN-3 workstation using the C language. The results are given to show the correctness of the theoretical analysis.<>