A Performance Evaluation of Periodic Signal Analysis by ARS Compared with Frequency Analysis by FFT. Issue 5 (1st September 2020)

• Record Type: Journal Article
• Authors: Takao, Ryota; Kamiya, Yukihiro
• Is Part Of: SICE journal of control, measurement, and system integration. Volume 13:Issue 5(2020)
• Page Start: 240
• Page End: 248
• Publication Date: 2020-09-01
• Subjects: accumulation for real-time serial-to-parallel converter -- fast Fourier transform -- Internet of Things -- edge computing -- frequency analysis
• DOI: 10.9746/jcmsi.13.240
• Languages: English
• ISSNs: 1882-4889

Abstract

Abstract : 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.