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Optimal signal reconstruction based on the Fourier decomposition method

机译:基于傅里叶分解法的最优信号重构

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The Fourier decomposition method (FDM) is the newest time-frequency-energy analysis tool for signals. Using the FDM, any signal can be represented by the sum of a small number of band-limited orthogonal functions termed Fourier intrinsic band functions (FIBFs). In its present form, however, the FDM is not based on an optimality criterion. The lack of optimality limits the signal recovery capability of the FDM in the presence of disturbances. To find a solution to this limitation and therefore to enhance the capability of the FDM, this paper proposes to adapt two thoughts that are previously applied for the empirical mode decomposition, to the FDM. The other contribution of this paper is that we propose faster procedures than the conventional FDM in finding the FIBFs of a given signal. Simulations show that the proposed approaches result in satisfactory performance in reconstructing the original signal under undesired disturbances.
机译:傅里叶分解法(FDM)是最新的信号时频能量分析工具。使用FDM,任何信号都可以由称为傅立叶本征频带函数(FIBF)的少数频带有限的正交函数之和表示。然而,以其当前形式,FDM不是基于最优性标准。缺乏最优性限制了在存在干扰的情况下FDM的信号恢复能力。为了找到解决此限制的方法,从而提高FDM的功能,本文提出将先前应用于经验模式分解的两种思想应用于FDM。本文的另一个贡献是,在寻找给定信号的FIBF时,我们提出了比常规FDM更快的过程。仿真表明,所提出的方法在不希望有的干扰下重建原始信号具有令人满意的性能。

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