首页> 外文期刊>Journal of symbolic computation >Probabilistic analysis of Wiedemann's algorithm for minimal polynomial computation
【24h】

Probabilistic analysis of Wiedemann's algorithm for minimal polynomial computation

机译:最小多项式计算的Wiedemann算法的概率分析

获取原文
获取原文并翻译 | 示例
           

摘要

Blackbox algorithms for linear algebra problems start with projection of the sequence of powers of a matrix to a sequence of vectors (Lanczos), a sequence of scalars (Wiedemann) or a sequence of smaller matrices (block methods). Such algorithms usually depend on the minimal polynomial of the resulting sequence being that of the given matrix. Here exact formulas are given for the probability that this occurs. They are based on the generalized Jordan normal form (direct sum of companion matrices of the elementary divisors) of the matrix. Sharp bounds follow from this for matrices of unknown elementary divisors. The bounds are valid for all finite field sizes and show that a small blocking factor can give high probability of success for all cardinalities and matrix dimensions. (C) 2015 Elsevier Ltd. All rights reserved.
机译:用于线性代数问题的黑盒算法始于将矩阵的幂序列投影到矢量序列(Lanczos),标量序列(Wiedemann)或较小矩阵的序列(块方法)。这样的算法通常取决于所得序列的最小多项式是给定矩阵的最小多项式。这里给出了发生这种情况的概率的精确公式。它们基于矩阵的广义约旦范式(基本除数的伴随矩阵的直接和)。对于未知的基本除数的矩阵,由此产生清晰的边界。该边界对所有有限域大小均有效,并且表明较小的阻塞因子可以为所有基数和矩阵维提供成功的高概率。 (C)2015 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号