{"title":"基于矩阵半张量积的模糊神经网络设计","authors":"Pengsheng Li","doi":"10.1117/12.2679164","DOIUrl":null,"url":null,"abstract":"Fuzzy neural network system is composed of fuzzy system and neural network system. In fuzzy the neural network system, the fuzzy logic system and the neural network system can play their respective advantages to achieve functional complementarity. In this paper, a fuzzy system based on semi-tensor product is proposed. Then fuzzy system and neural network are designed for hybrid control. Finally, the corresponding algorithm is proposed. The simulation results show that this method can shorten the control time of the system and improve the control effect.","PeriodicalId":301595,"journal":{"name":"Conference on Pure, Applied, and Computational Mathematics","volume":"06 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design of fuzzy neural network based on matrix semi-tensor product\",\"authors\":\"Pengsheng Li\",\"doi\":\"10.1117/12.2679164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fuzzy neural network system is composed of fuzzy system and neural network system. In fuzzy the neural network system, the fuzzy logic system and the neural network system can play their respective advantages to achieve functional complementarity. In this paper, a fuzzy system based on semi-tensor product is proposed. Then fuzzy system and neural network are designed for hybrid control. Finally, the corresponding algorithm is proposed. The simulation results show that this method can shorten the control time of the system and improve the control effect.\",\"PeriodicalId\":301595,\"journal\":{\"name\":\"Conference on Pure, Applied, and Computational Mathematics\",\"volume\":\"06 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference on Pure, Applied, and Computational Mathematics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2679164\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference on Pure, Applied, and Computational Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2679164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of fuzzy neural network based on matrix semi-tensor product
Fuzzy neural network system is composed of fuzzy system and neural network system. In fuzzy the neural network system, the fuzzy logic system and the neural network system can play their respective advantages to achieve functional complementarity. In this paper, a fuzzy system based on semi-tensor product is proposed. Then fuzzy system and neural network are designed for hybrid control. Finally, the corresponding algorithm is proposed. The simulation results show that this method can shorten the control time of the system and improve the control effect.
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