Results 181 to 190 of about 522,371 (218)
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An algorithm for constructing a class of Padé approximants of vector functions

Applied Numerical Mathematics, 1997
A matrix of polynomials \(Q_{m,n}=\left(\begin{smallmatrix} Q_{(m,n)_1} & 0\\ Q_{(m,n)_2} & Q_{(m,n)_1}\end{smallmatrix}\right)\) is considered. Expressions of the components are given. Algorithms are derived for constructing approximants for \(Q_{m,n}\). Two recurrence relations between the elements of adjacent systems are found.
openaire   +2 more sources

Polynomial Approximation of Functions: Historical Perspective and New Tools

International Journal of Computers for Mathematical Learning, 2003
Ivy Kidron
semanticscholar   +1 more source

Synthesizing Ranking Functions from Bits and Pieces

International Conference on Tools and Algorithms for Construction and Analysis of Systems, 2016
Caterina Urban   +2 more
semanticscholar   +1 more source

Surface-tracing approximation by basis functions and its applications to neural networks

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium, 2000
Yoshifusa Ito
semanticscholar   +1 more source

Decay bounds and \(O(n)\) algorithms for approximating functions of sparse matrices

2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Benzi, Michele, Razouk, Nader
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An optimal algorithm for finding the roots of an approximately computed function

USSR Computational Mathematics and Mathematical Physics, 1968
Abstract IN a wide range of practical and computational problems we have to find the roots of a function which can only be computed approximately for given values of its argument. Examples include the boundary value problem for a nonlinear system of differential equations, solved by specifying missing initial conditions (at one end), or the problem ...
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Approximate leave-one-out error estimation for learning with smooth, strictly convex margin loss functions

Proceedings of the 2004 14th IEEE Signal Processing Society Workshop Machine Learning for Signal Processing, 2004., 2004
C. Diehl
semanticscholar   +1 more source

New algorithms for the approximation of fixed points and fractal functions

Chaos, Solitons & Fractals
This article is devoted to explore the abilities of an iterative scheme for the approximation of fixed points of self-maps, called the N-algorithm, defined in a previous paper. In a first part of the article, the algorithm is modified in order to consider operators with asymptotic properties, namely nearly uniform contractions and nearly asymptotically
openaire   +3 more sources

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