{"title":"在线控制系统的神经模糊模型","authors":"Sergey M. Morozov, M. Kupriyanov","doi":"10.1109/scm55405.2022.9794864","DOIUrl":null,"url":null,"abstract":"Embedded systems development is a very important area. Devices must provide specific electrical signals. In-circuit control system is able to increase the quality of output or in-circuit signals, which is essential for devices in specific areas. Neuro-fuzzy systems provide an intellectual baseline for developing effective subsystems for signals’ control. Neuro-fizzy model for establishing in-circuit control is provided.","PeriodicalId":162457,"journal":{"name":"2022 XXV International Conference on Soft Computing and Measurements (SCM)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Neuro-fuzzy Model for In-circuit Control Systems\",\"authors\":\"Sergey M. Morozov, M. Kupriyanov\",\"doi\":\"10.1109/scm55405.2022.9794864\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Embedded systems development is a very important area. Devices must provide specific electrical signals. In-circuit control system is able to increase the quality of output or in-circuit signals, which is essential for devices in specific areas. Neuro-fuzzy systems provide an intellectual baseline for developing effective subsystems for signals’ control. Neuro-fizzy model for establishing in-circuit control is provided.\",\"PeriodicalId\":162457,\"journal\":{\"name\":\"2022 XXV International Conference on Soft Computing and Measurements (SCM)\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 XXV International Conference on Soft Computing and Measurements (SCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/scm55405.2022.9794864\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 XXV International Conference on Soft Computing and Measurements (SCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/scm55405.2022.9794864","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Embedded systems development is a very important area. Devices must provide specific electrical signals. In-circuit control system is able to increase the quality of output or in-circuit signals, which is essential for devices in specific areas. Neuro-fuzzy systems provide an intellectual baseline for developing effective subsystems for signals’ control. Neuro-fizzy model for establishing in-circuit control is provided.