Characterization of some convergent bivariate subdivision schemes with nonnegative masks

Characterization of some convergent bivariate subdivision schemes with nonnegative masks
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一些具有非负掩码的收敛双变量细分方案的表征

DOI:
10.1016/j.acha.2019.09.004
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发表时间:
2020-05
影响因子:
2.5
通讯作者:
Cheng Li
Cheng Li
中科院分区:
数学1区
文献类型:
--
作者:
Cheng Li

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已知具有非负掩码的多元细分格式的收敛性可以通过由该掩码导出的行随机矩阵的某些有限乘积是否具有正列来表征。然而,这些产品的数量是指数相对于矩阵的大小。对于非负的单变量细分,这个问题完全解决。因此,在这种情况下的收敛可以在线性时间内相对于方阵的大小进行检查。本文利用方阵的所谓连通性,证明了某些二元非负细分格式收敛的充要条件。此外,连接性可以在线性时间内相对于该矩阵的大小进行检查。
Knowing that the convergence of a multivariate subdivision scheme with a nonnegative mask can be characterized by whether or not some finite products of row-stochastic matrices induced by this mask have a positive column. However, the number of those products is exponential with respect to the size of matrices. For nonnegative univariate subdivision, this problem is completely solved. Thus, the convergence in this case can be checked in linear time with respect to the size of a square matrix. This paper will demonstrate the necessary and sufficient conditions for the convergence of some nonnegative bivariate subdivision schemes by means of the so-called connectivity of a square matrix, which is derived by a given mask. Moreover, the connectivity can be examined in linear time with respect to the size of this matrix.
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