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A Riemannian inexact Newton‐CG method for stochastic inverse singular value problems
Numerical Linear Algebra with Applications ( IF 4.3 ) Pub Date : 2020-09-23 , DOI: 10.1002/nla.2336
Ru‐Ru Ma 1 , Zheng‐Jian Bai 2
Affiliation  

In this article, we consider the stochastic inverse singular value problem (ISVP) of constructing a stochastic matrix from the prescribed realizable singular values. We propose a Riemannian inexact Newton‐CG method with various choices of forcing terms for solving the stochastic ISVP. We show the proposed method converges linearly or superlinearly for different forcing terms under some assumptions. We also extend the proposed method to the case of prescribed entries. Finally, we report some numerical results to demonstrate the effectiveness of the proposed method.

中文翻译:

随机反奇异值问题的黎曼不精确牛顿-CG方法

在本文中,我们考虑了从规定的可实现奇异值构造随机矩阵的随机逆奇异值问题(ISVP)。我们提出了一种黎曼不精确牛顿-CG方法,该方法具有多种强迫项来解决随机ISVP。我们显示了在某些假设下,对于不同的强迫项,该方法线性或超线性收敛。我们还将提议的方法扩展到规定条目的情况。最后,我们报告一些数值结果,以证明该方法的有效性。
更新日期:2020-12-02
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