{"title":"基于辨识网络和自适应网络的动态系统网络体系结构逆建模","authors":"T. Kimoto, Y. Yaginuma, S. Nagata, K. Asakawa","doi":"10.1109/IJCNN.1991.170460","DOIUrl":null,"url":null,"abstract":"The authors describe a neural network architecture enabling inverse modeling of a nonlinear dynamical system. It consists of two neural networks, a system identification network and an adaptation network. The effectiveness of the proposed network architecture is examined by applying it to a digital mobile communication adaptive equalizer. In digital mobile communication, the problem of multipath fading caused by vehicular movement becomes a nonlinear dynamical system. The proposed network architecture is able to obtain an inverse model of such transmission channels and attain equalization of signal distortions. The performance of the proposed adaptive equalizer was evaluated by computer simulation. The bit error rate was found to decrease by one-third compared to that without an equalizer.<<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":"1","resultStr":"{\"title\":\"Inverse modeling of dynamical system-network architecture with identification network and adaptation network\",\"authors\":\"T. Kimoto, Y. Yaginuma, S. Nagata, K. Asakawa\",\"doi\":\"10.1109/IJCNN.1991.170460\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors describe a neural network architecture enabling inverse modeling of a nonlinear dynamical system. It consists of two neural networks, a system identification network and an adaptation network. The effectiveness of the proposed network architecture is examined by applying it to a digital mobile communication adaptive equalizer. In digital mobile communication, the problem of multipath fading caused by vehicular movement becomes a nonlinear dynamical system. The proposed network architecture is able to obtain an inverse model of such transmission channels and attain equalization of signal distortions. The performance of the proposed adaptive equalizer was evaluated by computer simulation. The bit error rate was found to decrease by one-third compared to that without an equalizer.<<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\":\"1\",\"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.1991.170460\",\"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.1991.170460","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Inverse modeling of dynamical system-network architecture with identification network and adaptation network
The authors describe a neural network architecture enabling inverse modeling of a nonlinear dynamical system. It consists of two neural networks, a system identification network and an adaptation network. The effectiveness of the proposed network architecture is examined by applying it to a digital mobile communication adaptive equalizer. In digital mobile communication, the problem of multipath fading caused by vehicular movement becomes a nonlinear dynamical system. The proposed network architecture is able to obtain an inverse model of such transmission channels and attain equalization of signal distortions. The performance of the proposed adaptive equalizer was evaluated by computer simulation. The bit error rate was found to decrease by one-third compared to that without an equalizer.<>