{"title":"基于步长控制的微波测量频率采样算法","authors":"C. Rosca, N. Paraschiv","doi":"10.1109/ECAI.2016.7861104","DOIUrl":null,"url":null,"abstract":"Extending the microwave frequency measurement from very low to very high frequency requires improvements for the acquisition time. In this paper, a new sampling algorithm is presented with the main purpose to reduce the acquisition time by using a limited number of samples. The adaptive algorithm proposed in this paper computes only a limited number of samples and then reconstructs the entire circuit response using the interpolation model. This method uses an adaptive step-size control and has the initial step and the error predefined. The algorithm evaluates the difference between two consecutive S parameters. The adaptive step-size algorithm assumes that, when the distance between the current S parameter value and the previous one decreases (below a threshold ∊), the exploration step-size may be increased up to a limit in order to keep the step-size to a moderate value. Otherwise, it might overlook major S parameter variations. The biggest challenge here is represented by the correlation between S parameter domain, frequency domain and scaling values. This algorithm automatically finds the number of points needed to accurately evaluate high S parameters variations and it has a high speed computing.","PeriodicalId":122809,"journal":{"name":"2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Frequency sampling algorithm applied in microwave measurements based on step-size control method\",\"authors\":\"C. Rosca, N. Paraschiv\",\"doi\":\"10.1109/ECAI.2016.7861104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Extending the microwave frequency measurement from very low to very high frequency requires improvements for the acquisition time. In this paper, a new sampling algorithm is presented with the main purpose to reduce the acquisition time by using a limited number of samples. The adaptive algorithm proposed in this paper computes only a limited number of samples and then reconstructs the entire circuit response using the interpolation model. This method uses an adaptive step-size control and has the initial step and the error predefined. The algorithm evaluates the difference between two consecutive S parameters. The adaptive step-size algorithm assumes that, when the distance between the current S parameter value and the previous one decreases (below a threshold ∊), the exploration step-size may be increased up to a limit in order to keep the step-size to a moderate value. Otherwise, it might overlook major S parameter variations. The biggest challenge here is represented by the correlation between S parameter domain, frequency domain and scaling values. This algorithm automatically finds the number of points needed to accurately evaluate high S parameters variations and it has a high speed computing.\",\"PeriodicalId\":122809,\"journal\":{\"name\":\"2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECAI.2016.7861104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECAI.2016.7861104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Frequency sampling algorithm applied in microwave measurements based on step-size control method
Extending the microwave frequency measurement from very low to very high frequency requires improvements for the acquisition time. In this paper, a new sampling algorithm is presented with the main purpose to reduce the acquisition time by using a limited number of samples. The adaptive algorithm proposed in this paper computes only a limited number of samples and then reconstructs the entire circuit response using the interpolation model. This method uses an adaptive step-size control and has the initial step and the error predefined. The algorithm evaluates the difference between two consecutive S parameters. The adaptive step-size algorithm assumes that, when the distance between the current S parameter value and the previous one decreases (below a threshold ∊), the exploration step-size may be increased up to a limit in order to keep the step-size to a moderate value. Otherwise, it might overlook major S parameter variations. The biggest challenge here is represented by the correlation between S parameter domain, frequency domain and scaling values. This algorithm automatically finds the number of points needed to accurately evaluate high S parameters variations and it has a high speed computing.