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On the preconditioned biconjugate gradients for solving linear complex equations arising from finite elements

Michal Křížek, Jaroslav Mlýnek (1994)

Banach Center Publications

The paper analyses the biconjugate gradient algorithm and its preconditioned version for solving large systems of linear algebraic equations with nonsingular sparse complex matrices. Special emphasis is laid on symmetric matrices arising from discretization of complex partial differential equations by the finite element method.

On the randomized complexity of Banach space valued integration

Stefan Heinrich, Aicke Hinrichs (2014)

Studia Mathematica

We study the complexity of Banach space valued integration in the randomized setting. We are concerned with r times continuously differentiable functions on the d-dimensional unit cube Q, with values in a Banach space X, and investigate the relation of the optimal convergence rate to the geometry of X. It turns out that the nth minimal errors are bounded by c n - r / d - 1 + 1 / p if and only if X is of equal norm type p.

On the rational recursive sequence x n + 1 = α 0 x n + α 1 x n - l + α 2 x n - k β 0 x n + β 1 x n - l + β 2 x n - k

E. M. E. Zayed, M. A. El-Moneam (2010)

Mathematica Bohemica

The main objective of this paper is to study the boundedness character, the periodicity character, the convergence and the global stability of positive solutions of the difference equation x n + 1 = α 0 x n + α 1 x n - l + α 2 x n - k β 0 x n + β 1 x n - l + β 2 x n - k , n = 0 , 1 , 2 , where the coefficients α i , β i ( 0 , ) for i = 0 , 1 , 2 , and l , k are positive integers. The initial conditions x - k , , x - l , , x - 1 , x 0 are arbitrary positive real numbers such that l < k . Some numerical experiments are presented.

On the Recursive Estimation of the Location and of the Size of the Mode of a Probability Density

Djeddour, Khédidja, Mokkadem, Abdelkader, Pelletier, Mariane (2008)

Serdica Mathematical Journal

2000 Mathematics Subject Classification: 62G07, 62L20.Tsybakov [31] introduced the method of stochastic approximation to construct a recursive estimator of the location q of the mode of a probability density. The aim of this paper is to provide a companion algorithm to Tsybakov's algorithm, which allows to simultaneously recursively approximate the size m of the mode. We provide a precise study of the joint weak convergence rate of both estimators. Moreover, we introduce the averaging principle...

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