{"title":"利用邻域密度方程的导线长度估计技术","authors":"T. Hamada, Chung-Kuan Cheng, P. Chau","doi":"10.1109/DAC.1992.227861","DOIUrl":null,"url":null,"abstract":"A new wire length estimation technique is presented. Wire length distribution is modeled by wire density on a 2-D lattice. Assuming a pointwise independent branching process, the wire length distribution is found by solving the neighborhood density equations. For several industrial circuits tested, this technique achieved an estimation error of 9.0% with a maximum deviation of +16.3%, which compared favorably with other techniques recently proposed.<<ETX>>","PeriodicalId":162648,"journal":{"name":"[1992] Proceedings 29th ACM/IEEE Design Automation Conference","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"47","resultStr":"{\"title\":\"A wire length estimation technique utilizing neighborhood density equations\",\"authors\":\"T. Hamada, Chung-Kuan Cheng, P. Chau\",\"doi\":\"10.1109/DAC.1992.227861\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new wire length estimation technique is presented. Wire length distribution is modeled by wire density on a 2-D lattice. Assuming a pointwise independent branching process, the wire length distribution is found by solving the neighborhood density equations. For several industrial circuits tested, this technique achieved an estimation error of 9.0% with a maximum deviation of +16.3%, which compared favorably with other techniques recently proposed.<<ETX>>\",\"PeriodicalId\":162648,\"journal\":{\"name\":\"[1992] Proceedings 29th ACM/IEEE Design Automation Conference\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"47\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1992] Proceedings 29th ACM/IEEE Design Automation Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DAC.1992.227861\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1992] Proceedings 29th ACM/IEEE Design Automation Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DAC.1992.227861","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A wire length estimation technique utilizing neighborhood density equations
A new wire length estimation technique is presented. Wire length distribution is modeled by wire density on a 2-D lattice. Assuming a pointwise independent branching process, the wire length distribution is found by solving the neighborhood density equations. For several industrial circuits tested, this technique achieved an estimation error of 9.0% with a maximum deviation of +16.3%, which compared favorably with other techniques recently proposed.<>