Singular value decomposition in extended double precision arithmetic
نویسندگان
چکیده
Abstract A well-known and successful algorithm to compute the singular value decomposition (SVD) of a matrix was published by Golub Reinsch ( Numer. Math. 14:403–420, 1970), together with an implementation in Algol. We give updated extended double precision arithmetic C programming language. Extended is native for Intel x86 processors provides improved accuracy at full hardware speed. The complete program computing SVD listed. Additionally, comprehensive explanation original 1970) given elementary level without referring more general results Francis Comput. J. 4:265–271, 1961, 1962).
منابع مشابه
پیشنهاد روش جدیدی برای محاسبه polynomial singular value decomposition ) psvd )
در این پایان نامه به معرفی روشهای مختلف محاسبه psvd می پردازیم. بخشی از این روشها به بررسی روشهای مختلف محاسبه psvd در مقالات مطالعه شده می پردازد که می توان به محاسبهpsvd با استفاده از الگوریتمهای pqrd و pevd و sbr2 و محاسبه psvd براساس تکنیک kogbetliantz و روش پارامتریک برای محاسبه psvd اشاره نمود. بخش بعدی نیز به بررسی روشهای مستقیم پیشنهادی محاسبه psvd برای ماتریسهای 2×2و2× n و n×2 و 3× n و...
15 صفحه اولThe Singular Value Decomposition in the Extended Max Algebra ∗
First we establish a connection between the field of the real numbers and the extended max algebra, based on asymptotic equivalences. Next we propose a further extension of the extended max algebra that will correspond to the field of the complex numbers. Finally we use the analogy between the field of the real numbers and the extended max algebra to define the singular value decomposition of a...
متن کاملSingular Value Decomposition (SVD) and Generalized Singular Value Decomposition (GSVD)
The singular value decomposition (SVD) is a generalization of the eigen-decomposition which can be used to analyze rectangular matrices (the eigen-decomposition is definedonly for squaredmatrices). By analogy with the eigen-decomposition, which decomposes a matrix into two simple matrices, the main idea of the SVD is to decompose a rectangular matrix into three simple matrices: Two orthogonal m...
متن کاملSingular Value Decomposition Learning on Double Stiefel Manifold
The aim of this paper is to present a unifying view of four SVD-neural-computation techniques found in the scientific literature and to present some theoretical results on their behavior. The considered SVD neural algorithms are shown to arise as Riemannian-gradient flows on double Stiefel manifold and their geometric and dynamical properties are investigated with the help of differential geome...
متن کاملModified Adomian Decomposition Method for Double Singular Boundary Value Problems
where f(t),g(t), and h(t) are known continuous functions of t in the interval (0,1). Here N(u) is a nonlinear function of u. Let the above equation be singular at these two boundary value points t= 0,1. Scientists and engineers are interested in singular BVPs because they arise in a wide range of applications, such as in chemical engineering, mechanical engineering, nuclear industry, and nonlin...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Numerical Algorithms
سال: 2022
ISSN: ['1017-1398', '1572-9265']
DOI: https://doi.org/10.1007/s11075-022-01459-9