Displaying 181 – 200 of 1111

Showing per page

On consistency, stability and convergence of staggered solution procedures

Ewa Turska, Bernardo A. Schrefler (1994)

Atti della Accademia Nazionale dei Lincei. Classe di Scienze Fisiche, Matematiche e Naturali. Rendiconti Lincei. Matematica e Applicazioni

The simultaneous and staggered procedures of solving a partitioned form of a coupled system of ordinary differential equations are presented. Formulas for errors are compared. Counter-examples for convergence with a constant number of iterations at each time step are given.

On convergence of kernel density estimates in particle filtering

David Coufal (2016)

Kybernetika

The paper deals with kernel density estimates of filtering densities in the particle filter. The convergence of the estimates is investigated by means of Fourier analysis. It is shown that the estimates converge to the theoretical filtering densities in the mean integrated squared error. An upper bound on the convergence rate is given. The result is provided under a certain assumption on the Sobolev character of the filtering densities. A sufficient condition is presented for the persistence of...

On convergence of quadrature-differences method for linear singular integro-differential equations on the interval

A. I. Fedotov (2001)

Archivum Mathematicum

Here we propose and justify the quadrature-differences method for the full linear singular integro-differential equations with Cauchy kernel on the interval ( - 1 , 1 ) . We consider equations of zero, positive and negative indices. It is shown, that the method converges to exact solution and the error estimate depends on the sharpness of derivative approximation and the smoothness of the coefficients and the right-hand side of the equation.

On convergence of the empirical mean method for non-identically distributed random vectors

E. Gordienko, J. Ruiz de Chávez, E. Zaitseva (2014)

Applicationes Mathematicae

We consider the following version of the standard problem of empirical estimates in stochastic optimization. We assume that the underlying random vectors are independent and not necessarily identically distributed but that they satisfy a "slow variation" condition in the sense of the definition given in this paper. We show that these assumptions along with the usual restrictions (boundedness and equicontinuity) on a class of functions allow one to use the empirical mean method to obtain a consistent...

On decomposition of k-tridiagonal ℓ-Toeplitz matrices and its applications

A. Ohashi, T. Sogabe, T.S. Usuda (2015)

Special Matrices

We consider a k-tridiagonal ℓ-Toeplitz matrix as one of generalizations of a tridiagonal Toeplitz matrix. In the present paper, we provide a decomposition of the matrix under a certain condition. By the decomposition, the matrix is easily analyzed since one only needs to analyze the small matrix obtained from the decomposition. Using the decomposition, eigenpairs and arbitrary integer powers of the matrix are easily shown as applications.

Currently displaying 181 – 200 of 1111