Improvements to the Sliding Discrete Fourier Transform Algorithm [Tips & Tricks]

Autor:	Carl Q. Howard, Richard G. Lyons
Rok vydání:	2021
Předmět:	Computer science Simple (abstract algebra) Applied Mathematics Signal Processing Range (statistics) Zero (complex analysis) Sample (statistics) Electrical and Electronic Engineering Sliding discrete fourier transform Algorithm Signal Cycle per second Scalar Value
Zdroj:	IEEE Signal Processing Magazine. 38:119-127
ISSN:	1558-0792 1053-5888
DOI:	10.1109/msp.2021.3075416
Popis:	This article presents two networks that improve upon the behavior and performance of previously published sliding discrete Fourier transform (SDFT) algorithms. The proposed networks are structurally simple, computationally efficient, guaranteed stable networks used for real-time sliding spectrum analysis. The first real-time network computes one spectral output sample, equal to a singlebin output of an N-point DFT, for each input signal sample. The second real-time network is frequency flexible, in that its analysis frequency can be any scalar value in the range of zero to one-half the input data sample rate measured in cycles per second.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c0121b2d313a38ea920a3a54bdf0a00c https://doi.org/10.1109/msp.2021.3075416 Zobrazit plný text záznamu