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首页> 外文期刊>The Journal of Nonlinear Sciences and its Applications >On the local convergence of Gargantini-Farmer-Loizou method for simultaneous approximation of multiple polynomial zeros
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On the local convergence of Gargantini-Farmer-Loizou method for simultaneous approximation of multiple polynomial zeros

机译:多重多项式零点同时逼近的Gargantini-Farmer-Loizou方法的局部收敛性

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The paper deals with a well known iterative method for simultaneous computation of all zeros (of known multiplicities) of a polynomial with coefficients in a valued field.This method was independently introduced by Farmer and Loizou [M. R. Farmer, G. Loizou,Math. Proc. Cambridge Philos. Soc., ({f 82}) (1977), 427--437] and Gargantini [I. Gargantini,SIAM J. Numer. Anal., ({f 15}) (1978), 497--510].If all zeros of the polynomial are simple, the method coincides with the famous Ehrlich's method [L. W. Ehrlich,Commun. ACM, ({f 10}) (1967), 107--108].We provide two types of local convergence results for the Gargantini-Farmer-Loizou method.The first main result improves the results of [N. V. Kyurkchiev, A. Andreev, V. Popov, Ann. Univ. Sofia Fac. Math. Mech., ({f 78}) (1984), 178--185] and [A. I. Iliev, C. R. Acad. Bulg. Sci., ({f 49}) (1996), 23--26] for this method. Both main results of the paper generalize the results of Proinov [P. D. Proinov, Calcolo, ({f 53}) (2016), 413--426] for Ehrlich's method. The results in the present paper are obtained by applying a new approach for convergence analysis of Picard type iterative methods in finite-dimensional vector spaces.
机译:本文涉及一种众所周知的迭代方法,用于同时计算值字段中具有系数的多项式的所有零(已知多重性)。该方法由Farmer和Loizou [M. R. Farmer,G。Loizou,数学。进程剑桥Philos。 Soc。,({ bf 82} )(1977),427--437]和Gargantini [I. Gargantini,SIAM J. Numer。 Anal。,({ bf 15} )(1978),497--510]。如果多项式的所有零都是简单的,则该方法与著名的Ehrlich方法[L. W. Ehrlich,共同ACM,({ bf 10} )(1967),107--108]。对于Gargantini-Farmer-Loizou方法,我们提供了两种类型的局部收敛结果。第一个主要结果改进了[N. V.Kyurkchiev,A.Andreev,V.Popov,Ann。大学索非亚数学。机械,({ bf 78} )(1984),178--185]和[A. I. Iliev,C。R. Acad。宝格Sci。,({ bf 49} )(1996),23--26]。本文的两个主要结果都推广了Proinov [P. D. Proinov,Calcolo,({ bf 53} )(2016),413--426]。本文的结果是通过采用一种新方法对有限维向量空间中的Picard型迭代方法进行收敛性分析而获得的。

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