牛顿迭代:从数值学到组合学再回来

B. Salvy
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引用次数: 0

摘要

讲座将探讨各种新旧算法,其效率归结为牛顿迭代的快速收敛。在数值上,在接近根的地方,每次迭代正确数字的数量翻倍。当处理幂级数时,选择一个好的初始点的问题消失了,每次迭代系数的数量增加了一倍。这种观察,加上快速乘法,导致了各种符号计算问题的快速算法,从代数级数的经典结果到最近的微分方程系统的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Newton Iteration: From Numerics to Combinatorics, and Back
The talk will explore a variety of old and recent algorithms whose efficiency boils down to the fast convergence of Newton iteration. Numerically, and close to the root, the number of correct digits is doubled at each iteration. When working with power series, the problem of picking a good initial point disappears and the number of coefficients is doubled at each iteration. This observation, coupled with fast multiplication, leads to fast algorithms in a variety of problems of symbolic computation, ranging from classical results on algebraic series to more recent ones on systems of differential equations.
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