一种新的基于拐点的筛选方法

Hong Hong, Heng Zhao, Yusheng Li, Chen Gu, Xiaohua Zhu
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引用次数: 1

摘要

本文提出了一种基于拐点(S-BIP)的经验模态分解筛选方法,以分离一个倍频内频率重叠的模态。对一些典型合成信号的数值分析表明,该方法可以将固有模态函数的上下限之比从2降低到1.3,从而减轻了尺度混频效应,提高了频率分辨率。此外,与现有方案相比,该方法显著降低了计算复杂度,有利于在实际信号处理中推广应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new sifting method based on inflection point
A new sifting method based on inflection point (S-BIP) for empirical mode decomposition is proposed in this paper, aiming at separating the modes with frequencies overlapped in an octave. The numerical analysis for some typical synthetic signals shows that the new approach can significantly reduce the ratio of the upper and lower frequency limits of an intrinsic mode function from 2 to 1.3, which mitigating the scale-mixing effect and enhancing the power of frequency resolution. In addition, as compared to the existing schemes, the proposed method significantly reduces computational complexity and benefit its spread application in real signal processing.
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