{"title":"基于双线性变换的proony和Shank方法的降阶建模","authors":"M. Mansour, A. Mehrotra","doi":"10.1109/ISQED.2003.1194749","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new model-order reduction technique for linear dynamic systems. The idea behind this technique is to transform the dynamic system function from the s-domain into the z-domain via the bilinear transformation, then use Prony's or Shank's least-squares approximation methods instead of the commonly employed Pade approximation method, and finally transform the reduced system back into the s-domain using the inverse bilinear transformation. Simulation results for large practical systems show that this technique based on Prony's and Shank's methods give much higher accuracy than the traditional Pade method. and result in lower-order approximations with negligible increase in simulation time.","PeriodicalId":448890,"journal":{"name":"Fourth International Symposium on Quality Electronic Design, 2003. Proceedings.","volume":"280 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Reduced-order modeling based on Prony's and Shank's methods via the bilinear transformation\",\"authors\":\"M. Mansour, A. Mehrotra\",\"doi\":\"10.1109/ISQED.2003.1194749\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new model-order reduction technique for linear dynamic systems. The idea behind this technique is to transform the dynamic system function from the s-domain into the z-domain via the bilinear transformation, then use Prony's or Shank's least-squares approximation methods instead of the commonly employed Pade approximation method, and finally transform the reduced system back into the s-domain using the inverse bilinear transformation. Simulation results for large practical systems show that this technique based on Prony's and Shank's methods give much higher accuracy than the traditional Pade method. and result in lower-order approximations with negligible increase in simulation time.\",\"PeriodicalId\":448890,\"journal\":{\"name\":\"Fourth International Symposium on Quality Electronic Design, 2003. Proceedings.\",\"volume\":\"280 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fourth International Symposium on Quality Electronic Design, 2003. Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISQED.2003.1194749\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fourth International Symposium on Quality Electronic Design, 2003. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISQED.2003.1194749","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reduced-order modeling based on Prony's and Shank's methods via the bilinear transformation
In this paper, we propose a new model-order reduction technique for linear dynamic systems. The idea behind this technique is to transform the dynamic system function from the s-domain into the z-domain via the bilinear transformation, then use Prony's or Shank's least-squares approximation methods instead of the commonly employed Pade approximation method, and finally transform the reduced system back into the s-domain using the inverse bilinear transformation. Simulation results for large practical systems show that this technique based on Prony's and Shank's methods give much higher accuracy than the traditional Pade method. and result in lower-order approximations with negligible increase in simulation time.