周期紧支撑径向基函数对BEMD的优化
doi: 10.3724/SP.J.1146.2006.00849
The Improvement of the BEMD Using Compactly Supported RBF
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摘要: 该文提出了一种优化二维经验模式分解 (Bidimensional Empirical Mode Decomposition, BEMD)的方法。周期紧支撑径向基函数满足不同程度光滑性，能够容忍数据点集不规则性，避免出现上冲现象，而且大大减少了计算量和存储量，特别是能够消除Gibbs现象，抑制边界效应。实验证实本文提出的利用周期紧支撑径向基函数改进BEMD方法，能够获得较好的BEMD分解结果。Abstract: In this paper, a method is proposed which uses the Radial Basis Function (RBF) to improve the Bidimensional Empirical Mode Decomposition (BEMD). The mirror compactly supported RBF not only has the precision of interpolation and suppresses the boundary effect, but also has fast computation. Experiments indicate that the method in this paper can gain better decompositions.
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