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Convergence of univariate non-stationary subdivision schemes via asymptotic similarity

机译:通过渐近相似性收敛的单变量非平稳细分方案

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摘要

A new equivalence notion between non-stationary subdivision schemes, termed asymptotic similarity, which is weaker than asymptotic equivalence, is introduced and studied. It is known that asymptotic equivalence between a non-stationary subdivision scheme and a convergent stationary scheme guarantees the convergence of the non-stationary scheme. We show that for non-stationary schemes reproducing constants, the condition of asymptotic equivalence can be relaxed to asymptotic similarity. This result applies to a wide class of non-stationary schemes.
机译:引入并研究了非平稳细分方案之间的一种新的等价概念,即渐近相似性,它比渐近等价性弱。众所周知,非平稳细分方案和收敛平稳方案之间的渐近等价保证了非平稳方案的收敛。我们表明,对于非平稳方案重现常数,渐近等效条件可以放宽到渐近相似性。此结果适用于多种非平稳方案。

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