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Design of a recursive single-bin DFT algorithm for sparse spectrum analysis

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Abstract

Discrete Fourier transform (DFT) is the basic means of spectrum analysis in the field of digital signal processing, and the fast Fourier transform (FFT) has become the most popular algorithm which decreases the computational complexity from quadratical to linearithmic. However, engineers are often challenged to detect a single or just a few of the frequency components. For this kind of sparse spectrum analysis, the FFT no longer has advantage because it always computes all the frequency components. This paper proposes a recursive single-bin DFT (RSB-DFT) algorithm to compute one specific frequency spectrum, whose theoretical derivation is elaborated and implementation steps are given as a flow diagram. A 16-point RSB-DFT calculation example is also given to exhibit computation process of the algorithm. An application example for bioimpedance spectroscopy (BIS) measurement demonstrates that the proposed RSB-DFT algorithm can compute specific single spectral lines accurately. The computation efficiency of the proposed RSB-DFT algorithm is demonstrated as the highest compared with the DFT, FFT, Goertzel algorithm, which means that the RSB-DFT algorithm has the potential to become an alternative and efficient tool for sparse spectrum analysis.

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Acknowledgements

This study has been supported by grants from the Scientific Research Plan of Education Bureau of Shaanxi Province (No. 16JK1370) and the Scientific Research Plan of Science and Technology Bureau of Shaanxi Province (2016GY-051).

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Authors and Affiliations

  1. School of Optoelectronic Engineering, Xi’an Technological University, Xi’an, 710021, Shaanxi, People’s Republic of China

    Wei Wang, Ying Tang, Xiongxing Zhang & Kening Wang

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  1. Wei Wang
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  2. Ying Tang
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  3. Xiongxing Zhang
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  4. Kening Wang
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Correspondence to Wei Wang.

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Wang, W., Tang, Y., Zhang, X. et al. Design of a recursive single-bin DFT algorithm for sparse spectrum analysis. Cluster Comput 20, 1483–1492 (2017). https://doi.org/10.1007/s10586-017-0866-8

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