混合光滑Besov类的m项逼近贪心型算法

Third International Conference on Natural Computation (ICNC 2007) Pub Date : 2007-08-24 DOI:10.1109/ICNC.2007.200

Peixin Ye, Qing He

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引用次数: 0

摘要

提出了一种最佳m项逼近下的贪婪型自适应压缩数值算法。该算法利用张量积小波基对Lq范数上混合光滑的周期Besov类函数给出渐近最优逼近。此外，它只依赖于函数f由张量积小波型基展开，而不依赖于q或f的任何特殊特征。

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An Greedy-type Algorithm in m-term Approximation For Besov Class with Mixed Smoothness

We propose an greedy-type adaptive compression numerical algorithm in best m-term approximation. This algorithm provides the asymptotically optimal approximation by tensor product wavelet-type basis for functions from periodic Besov class with mixed smoothness in the Lq norm. Moreover it depends only on the expansion of function f by tensor product wavelet-type basis but neither on q nor on any special features of f.

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Third International Conference on Natural Computation (ICNC 2007)

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