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An efficient algorithm for harmonic retrieval by combining blind source separation with wavelet packet decomposition

机译:盲源分离与小波包分解相结合的谐波检索有效算法

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In the present paper, we propose an efficient framework and algorithm for one dimensional harmonic retrieval problem in additive colored Gaussian or non-Gaussian noise when the frequencies of the harmonic signals are closely spaced in frequency domain. Our framework utilizes the wavelet packet (WP) method to the blind source separation (BSS) based harmonic retrieval model. Firstly, we establish the BSS based harmonic retrieval model in additive noise using only one mixed channel signal, at the same time, the fundamental principle of BSS based harmonics retrieval algorithm is analyzed in detail. Then, the harmonic retrieval algorithm is developed mainly using the WP decomposition approach, where the criterion is formed as the cumulant based approximation of the mutual information (MI) for the selection of optimal sub-bands of WP decomposition with the least-dependent components between the same nodes. Simulation results show that the proposed algorithm is able to retrieve the harmonic source signals and yield good performance. (C) 2015 Elsevier Inc. All rights reserved.
机译:在本文中,我们提出了一种有效的框架和算法,当谐波信号的频率在频域中间隔很近时,可以解决加色有色高斯或非高斯噪声中的一维谐波检索问题。我们的框架将小波包(WP)方法用于基于盲源分离(BSS)的谐波检索模型。首先,我们仅使用一个混合通道信号建立了基于BSS的加性噪声​​谐波检索模型,同时,详细分析了基于BSS的谐波检索算法的基本原理。然后,主要使用WP分解方法开发谐波检索算法,该准则的形成标准是互积(MI)的基于累积量的近似,用于选择WP分解之间具有最小相关成分的最佳子带。相同的节点。仿真结果表明,该算法能够检索谐波源信号,并具有良好的性能。 (C)2015 Elsevier Inc.保留所有权利。

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