{"title":"主要不变量的块维德曼概率分析","authors":"Gavin Harrison, Jeremy R. Johnson, B. D. Saunders","doi":"10.1145/3055282.3055294","DOIUrl":null,"url":null,"abstract":"The exact probability, dependent on the matrix structure, is given that the block Wiedemann algorithm correctly computes the leading invariant factors of a matrix. A tight lower bound, structure independent, is derived.","PeriodicalId":7093,"journal":{"name":"ACM Commun. Comput. Algebra","volume":"1 1","pages":"173-175"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Probabilistic analysis of block wiedemann for leading invariant factors\",\"authors\":\"Gavin Harrison, Jeremy R. Johnson, B. D. Saunders\",\"doi\":\"10.1145/3055282.3055294\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The exact probability, dependent on the matrix structure, is given that the block Wiedemann algorithm correctly computes the leading invariant factors of a matrix. A tight lower bound, structure independent, is derived.\",\"PeriodicalId\":7093,\"journal\":{\"name\":\"ACM Commun. Comput. Algebra\",\"volume\":\"1 1\",\"pages\":\"173-175\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Commun. Comput. Algebra\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3055282.3055294\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Commun. Comput. Algebra","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3055282.3055294","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Probabilistic analysis of block wiedemann for leading invariant factors
The exact probability, dependent on the matrix structure, is given that the block Wiedemann algorithm correctly computes the leading invariant factors of a matrix. A tight lower bound, structure independent, is derived.
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