A Performance Evaluation of Periodic Signal Analysis by ARS Compared with Frequency Analysis by FFT
A Performance Evaluation of Periodic Signal Analysis by ARS Compared with Frequency Analysis by FFT
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DOI：
10.9746/jcmsi.13.240
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发表时间：
2020-09
期刊：
影响因子：
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通讯作者：
Ryota Takao;Y. Kamiya
中科院分区：
文献类型：
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作者：
Ryota Takao;Y. Kamiya
实时串行-并行转换器（ARS）的累积已被提出作为用于信号分析的计算高效的方法。由于它只包括加法和少量除法，因此与快速傅立叶变换（FFT）相比，计算量大大减少。在本文中，我们澄清，ARS实现了更高的分辨率在低频段相比，FFT。此外，从分辨率的角度，从理论上阐明了ARS和FFT的选择准则。通过对ARS在低频段的性能分析，可以预期ARS是物联网中实现边缘计算的信号分析的有力工具。
Accumulation for real-time serial-to-parallel converter (ARS) has been proposed as a computationally-efficient method for signal analysis. Since it consists of additions and a few divisions only, it was shown that the computational load is drastically reduced compared with the fast Fourier transform (FFT). In this paper, we clarify that ARS achieves a higher resolution in low-frequency bands comparing with FFT. In addition, selection criteria between ARS and FFT are clarified theoretically in terms of the resolution. Through the performance analysis of ARS in low-frequency bands, it is expected that ARS is a powerful tool for signal analysis in the Internet of Things realizing the edge computing.