2019
Том 71
№ 6

All Issues

Deineka V. S.

Articles: 6
Article (Russian)

Necessary and Sufficient Conditions for the Existence of Weighted Singular-Valued Decompositions of Matrices with Singular Weights

Deineka V. S., Galba E. F., Sergienko I. V.

↓ Abstract   |   Full text (.pdf)

Ukr. Mat. Zh. - 2015. - 67, № 3. - pp. 406–426

A weighted singular-valued decomposition of matrices with singular weights is obtained by using orthogonal matrices. The necessary and sufficient conditions for the existence of the constructed weighted singular-valued decomposition are established. The indicated singular-valued decomposition of matrices is used to obtain a decomposition of their weighted pseudoinverse matrices and decompose them into matrix power series and products. The applications of these decompositions are discussed.

Article (Russian)

Existence and uniqueness of weighted pseudoinverse matrices and weighted normal pseudosolutions with singular weights

Deineka V. S., Galba E. F., Sergienko I. V.

↓ Abstract   |   Full text (.pdf)

Ukr. Mat. Zh. - 2011. - 63, № 1. - pp. 80-101

For one of definitions of weighted pseudoinversion with singular weights, necessary and sufficient conditions for the existence and uniqueness are obtained. Expansions of weighted pseudoinverse matrices in matrix power series and matrix power products are obtained. Relationship is established between the weighted pseudoinverse matrices and the weighted normal pseudosolutions. Iterative methods for the calculation of both weighted pseudoinverse matrices and weighted normal pseudosolutions are constructed.

Article (Russian)

Expansion of weighted pseudoinverse matrices with singular weights into matrix power products and iteration methods

Deineka V. S., Galba E. F., Sergienko I. V.

↓ Abstract   |   Full text (.pdf)

Ukr. Mat. Zh. - 2007. - 59, № 9. - pp. 1269–1289

We obtain expansions of weighted pseudoinverse matrices with singular weights into matrix power products with negative exponents and arbitrary positive parameters. We show that the rate of convergence of these expansions depends on a parameter. On the basis of the proposed expansions, we construct and investigate iteration methods with quadratic rate of convergence for the calculation of weighted pseudoinverse matrices and weighted normal pseudosolutions. Iteration methods for the calculation of weighted normal pseudosolutions are adapted to the solution of least-squares problems with constraints.

Article (Russian)

Expansion of Weighted Pseudoinverse Matrices in Matrix Power Products

Deineka V. S., Galba E. F., Sergienko I. V.

↓ Abstract   |   Full text (.pdf)

Ukr. Mat. Zh. - 2004. - 56, № 11. - pp. 1539-1556

On the basis of the Euler identity, we obtain expansions for weighted pseudoinverse matrices with positive-definite weights in infinite matrix power products of two types: with positive and negative exponents. We obtain estimates for the closeness of weighted pseudoinverse matrices and matrices obtained on the basis of a fixed number of factors of matrix power products and terms of matrix power series. We compare the rates of convergence of expansions of weighted pseudoinverse matrices in matrix power series and matrix power products to weighted pseudoinverse matrices. We consider problems of construction and comparison of iterative processes of computation of weighted pseudoinverse matrices on the basis of the obtained expansions of these matrices.

Article (Ukrainian)

Problems of Transmission with Inhomogeneous Principal Conjugation Conditions and High-Accuracy Numerical Algorithms for Their Discretization

Deineka V. S., Sergienko I. V.

↓ Abstract   |   Full text (.pdf)

Ukr. Mat. Zh. - 2002. - 54, № 2. - pp. 258-275

We construct new problems of transmission and high-accuracy computational algorithms for their discretization.

Article (Ukrainian)

Eigenvalue problems with discontinuous eigenfunctions and their numerical solutions

Deineka V. S., Sergienko I. V., Skopetskii V. V.

↓ Abstract   |   Full text (.pdf)

Ukr. Mat. Zh. - 1999. - 51, № 10. - pp. 1317–1323

We consider new eigenvalue problems with discontinuous eigenfunctions and construct computational algorithms whose accuracy is not worse than the accuracy of analogous known algorithms for problems with smooth eigenfunctions.