Convergence of subdivision schemes associated with nonnegative masks
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 418-430 |
Journal / Publication | SIAM Journal on Matrix Analysis and Applications |
Volume | 21 |
Issue number | 2 |
Publication status | Published - Oct 1999 |
Link(s)
Abstract
This paper is concerned with refinement equations of the type f = ∑ a(α)f(M · - α), α∈ℤs where f is the unknown function defined on the s-dimensional Euclidean space ℝs-a, a is a finitely supported sequence on ℤs, and M is an s × s dilation matrix with m := | det M|. The solution of a refinement equation can be obtained by using the subdivision scheme associated with the mask. In this paper we give a characterization for the convergence of the subdivision scheme when the mask is nonnegative. Our method is to relate the problem of convergence to m column-stochastic matrices induced by the mask. In this way, the convergence of the subdivision scheme can be determined in a finite number of steps by checking whether each finite product of those column-stochastic matrices has a positive row. As a consequence of our characterization, we show that the convergence of the subdivision scheme with a nonnegative mask depends only on the location of its positive coefficients. Several examples are provided to demonstrate the power and applicability of our approach.
Research Area(s)
- Convergent matrix products, Refinement equations, Stochastic matrices, Subdivision schemes
Citation Format(s)
Convergence of subdivision schemes associated with nonnegative masks. / Jia, Rong-Qing; Zhou, Ding-Xuan.
In: SIAM Journal on Matrix Analysis and Applications, Vol. 21, No. 2, 10.1999, p. 418-430.
In: SIAM Journal on Matrix Analysis and Applications, Vol. 21, No. 2, 10.1999, p. 418-430.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review