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首页> 外文期刊>SIAM Journal on Numerical Analysis >SMOOTHNESS ANALYSIS OF SUBDIVISION SCHEMES ONREGULAR GRIDS BY PROXIMITY
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SMOOTHNESS ANALYSIS OF SUBDIVISION SCHEMES ONREGULAR GRIDS BY PROXIMITY

机译:近似网格下细分方案的光滑度分析

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Subdivision is a powerful way of approximating a continuous object f(x,y) by a sequence ((S~lp_(i,j))i,j∈Z)l∈N of discrete data on finer and finer grids. The rule S that maps an approximation on a coarse grid S~lp to the approximation on the next finer grid S~(l+1)p is called a subdivision scheme. If for a given scheme S every continuous object f(x, y) constructed by S is of C~k smoothness, then S is said to have smoothness order k. Subdivision schemes are well understood if they are linear. However, for various applications the data have values in a manifold which is not a vector space (for example, when our data are positions of a moving rigid body). Under these circumstances, subdivision schemes become nonlinear and much harder to analyze. One way of analyzing such schemes is to relate them to a given linear scheme and to establish a so-called proximity condition between the two schemes, which helps in proving that the two schemes share the same smoothness. The present paper uses this method to show the C~1-smoothness of a wide class of nonlinear multivariate schemes.
机译:细分是一种通过在越来越细的网格上由离散数据的序列((S〜lp_(i,j))i,j∈Z)l∈N逼近连续对象f(x,y)的有效方法。将粗网格S_lp上的近似映射到下一细网格S_(l + 1)p上的近似的规则S被称为细分方案。如果对于给定的方案S,由S构造的每个连续对象f(x,y)具有Ck平滑度,则称S具有平滑度阶k。如果细分方案是线性的,则很好理解。但是,对于各种应用,数据在不是矢量空间的歧管中具有值(例如,当我们的数据是移动的刚体的位置时)。在这种情况下,细分方案变得非线性且难以分析。分析此类方案的一种方法是将它们与给定的线性方案相关联,并在两个方案之间建立所谓的邻近条件,这有助于证明两个方案具有相同的平滑度。本文使用这种方法来显示一类非线性多元方案的C〜1光滑度。

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