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Use of the Discrete Fourier Transform in the Measurement of Frequencies and Levels of Tones

Rife, D. C., Vincent, G. A.·1970·Bell System Technical Journal

Abstract

This paper considers the application of a digital computer and discrete Fourier transform (DFT) techniques to the measurement of signals known to comprise only single-frequency tones. We discuss the use of weighting functions to improve the effective selectivity of a measurement system that estimates the frequencies and levels of tones from the coefficients of their DFT. We present three classes of weighting functions which may be used to improve the inherent accuracy of such a system. The form of the weighting functions was chosen to minimize the amount of computer memory required, without using too much computer time. Several formulas are derived for estimating the frequency and level of a tone from its DFT coefficients. We chose the formulas to minimize computation time. Simulation results indicate that, through the use of a proper weighting function, a DFT measurement system that uses 512 samples taken at a sampling frequency of 7040 Hz can be designed so that the maximum error in the frequency estimates of two tones near 1000 Hz and separated by approximately 50 Hz is about 0.03 Hz. The corresponding maximum error in the level estimate is on the order of 0.03 dB.

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Metadata

Authors
Rife, D. C., & Vincent, G. A.
Venue
Bell System Technical Journal
Published
1970-02
Volume
49
Issue
2
Pages
197-228
ISSN
0005-8580 (ISSN-L)
OpenAlex
W2032233115
Cited by
389
References
0
FWCI
2.20
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Use of the Discrete Fourier Transform in the Measurement of Frequencies and Levels of Tones. https://app.cochat.ai/papers/10.1002/j.1538-7305.1970.tb01766.x
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Rife, D. C., & Vincent, G. A. (1970). Use of the Discrete Fourier Transform in the Measurement of Frequencies and Levels of Tones. Bell System Technical Journal. https://doi.org/10.1002/j.1538-7305.1970.tb01766.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.