{"title":"异型RFID天线神经空间映射建模研究进展","authors":"Shuxia Yan, Zhifeng Chen, Weiguang Shi, F. Feng","doi":"10.1109/APCAP56600.2022.10069453","DOIUrl":null,"url":null,"abstract":"With the development of technology, the radio frequence (RF) antenna gain estimation methods need to overcome some problems, such as complex modeling processes, long modeling cycles, and low model accuracy. The traditional methods are unable to meet modern device modeling requirements. This paper introduces an estimation framework, which combine neuro-space mapping (Neuro-SM) model with the particle swarm optimiser algorithm. Simulation results show that this method can improve the accuracy of existing models.","PeriodicalId":197691,"journal":{"name":"2022 IEEE 10th Asia-Pacific Conference on Antennas and Propagation (APCAP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Review of Neuro-Space Mapping Modeling for Heteromorphic RFID Antennas\",\"authors\":\"Shuxia Yan, Zhifeng Chen, Weiguang Shi, F. Feng\",\"doi\":\"10.1109/APCAP56600.2022.10069453\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the development of technology, the radio frequence (RF) antenna gain estimation methods need to overcome some problems, such as complex modeling processes, long modeling cycles, and low model accuracy. The traditional methods are unable to meet modern device modeling requirements. This paper introduces an estimation framework, which combine neuro-space mapping (Neuro-SM) model with the particle swarm optimiser algorithm. Simulation results show that this method can improve the accuracy of existing models.\",\"PeriodicalId\":197691,\"journal\":{\"name\":\"2022 IEEE 10th Asia-Pacific Conference on Antennas and Propagation (APCAP)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 10th Asia-Pacific Conference on Antennas and Propagation (APCAP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APCAP56600.2022.10069453\",\"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 IEEE 10th Asia-Pacific Conference on Antennas and Propagation (APCAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCAP56600.2022.10069453","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Review of Neuro-Space Mapping Modeling for Heteromorphic RFID Antennas
With the development of technology, the radio frequence (RF) antenna gain estimation methods need to overcome some problems, such as complex modeling processes, long modeling cycles, and low model accuracy. The traditional methods are unable to meet modern device modeling requirements. This paper introduces an estimation framework, which combine neuro-space mapping (Neuro-SM) model with the particle swarm optimiser algorithm. Simulation results show that this method can improve the accuracy of existing models.