{"title":"一种新的分数阶忆阻模拟器电路设计","authors":"Zehra Gulru Cam Taskiran, M. Taskiran","doi":"10.1109/INISTA.2019.8778386","DOIUrl":null,"url":null,"abstract":"In this study, a previously defined integer order memristor element equation has been modified and a similar form of fractional order memristor is given. In the resulting mathematical equation, frequency dependent pinched hysteresis curves are obtained. A memristance simulator circuit providing the proposed mathematical relationship is proposed. The proposed circuit can be implemented with the integrated circuit elements commercially available in the market. In recent years, due to the non-volatile memory, nonlocality, and weak singularity characteristics, fractional calculus has been successfully applied to ANN s. Thus, this circuit can be useful for physical realization of the fractional order neural networks.","PeriodicalId":262143,"journal":{"name":"2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A New Fractional Order Memristance Simulator Circuit Design\",\"authors\":\"Zehra Gulru Cam Taskiran, M. Taskiran\",\"doi\":\"10.1109/INISTA.2019.8778386\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, a previously defined integer order memristor element equation has been modified and a similar form of fractional order memristor is given. In the resulting mathematical equation, frequency dependent pinched hysteresis curves are obtained. A memristance simulator circuit providing the proposed mathematical relationship is proposed. The proposed circuit can be implemented with the integrated circuit elements commercially available in the market. In recent years, due to the non-volatile memory, nonlocality, and weak singularity characteristics, fractional calculus has been successfully applied to ANN s. Thus, this circuit can be useful for physical realization of the fractional order neural networks.\",\"PeriodicalId\":262143,\"journal\":{\"name\":\"2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INISTA.2019.8778386\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INISTA.2019.8778386","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Fractional Order Memristance Simulator Circuit Design
In this study, a previously defined integer order memristor element equation has been modified and a similar form of fractional order memristor is given. In the resulting mathematical equation, frequency dependent pinched hysteresis curves are obtained. A memristance simulator circuit providing the proposed mathematical relationship is proposed. The proposed circuit can be implemented with the integrated circuit elements commercially available in the market. In recent years, due to the non-volatile memory, nonlocality, and weak singularity characteristics, fractional calculus has been successfully applied to ANN s. Thus, this circuit can be useful for physical realization of the fractional order neural networks.