{"title":"基于投影的高效互联网络宏模型","authors":"M. Ma, R. Khazaka","doi":"10.1109/SPI.2005.1500939","DOIUrl":null,"url":null,"abstract":"This paper presents a projection based technique for obtaining reduced order macromodels of large multi-port interconnect networks. The proposed approach uses two levels of reduction and results in macromodels which are typically half the size of those obtained using traditional Krylov methods. The second level of reduction is based on singular value decomposition (SVD), is very simple to implement and can be easily extended to new applications. Examples are shown that demonstrate the accuracy and efficiency of this approach.","PeriodicalId":182291,"journal":{"name":"Proceedings. 9th IEEE Workshop on Signal Propagation on Interconnects, 2005.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Efficient projection based macromodel for interconnect networks\",\"authors\":\"M. Ma, R. Khazaka\",\"doi\":\"10.1109/SPI.2005.1500939\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a projection based technique for obtaining reduced order macromodels of large multi-port interconnect networks. The proposed approach uses two levels of reduction and results in macromodels which are typically half the size of those obtained using traditional Krylov methods. The second level of reduction is based on singular value decomposition (SVD), is very simple to implement and can be easily extended to new applications. Examples are shown that demonstrate the accuracy and efficiency of this approach.\",\"PeriodicalId\":182291,\"journal\":{\"name\":\"Proceedings. 9th IEEE Workshop on Signal Propagation on Interconnects, 2005.\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-05-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 9th IEEE Workshop on Signal Propagation on Interconnects, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPI.2005.1500939\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 9th IEEE Workshop on Signal Propagation on Interconnects, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPI.2005.1500939","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient projection based macromodel for interconnect networks
This paper presents a projection based technique for obtaining reduced order macromodels of large multi-port interconnect networks. The proposed approach uses two levels of reduction and results in macromodels which are typically half the size of those obtained using traditional Krylov methods. The second level of reduction is based on singular value decomposition (SVD), is very simple to implement and can be easily extended to new applications. Examples are shown that demonstrate the accuracy and efficiency of this approach.