Spectral Analysis (Discrete Fourier Transform)

2018 ◽  
pp. 389-398
2021 ◽  
Vol 10 (2) ◽  
Author(s):  
Pranesh Kumar ◽  
Arthur Western

The analysis of pulsars is a complicated procedure due to the influence of background radio waves. Special radio telescopes designed to detect pulsar signals have to employ many techniques to reconstruct interstellar signals and determine if they originated from a pulsating radio source. The Discrete Fourier Transform on its own has allowed astronomers to perform basic spectral analysis of potential pulsar signals. However, Radio Frequency Interference (RFI) makes the process of detecting and analyzing pulsars extremely difficult. This has forced astronomers to be creative in identifying and determining the specific characteristics of these unique rotating neutron stars. Astrophysicists have utilized algorithms such as the Fast Fourier Transform (FFT) to predict the spin period and harmonic frequencies of pulsars. However, FFT-based searches cannot be utilized alone because low-frequency pulsar signals go undetected in the presence of background radio noise. Astrophysicists must stack up pulses using the Fast Folding Algorithm (FFA) and utilize the coherent dedispersion technique to improve FFT sensitivity. The following research paper will discuss how the Discrete Fourier Transform is a useful technique for detecting radio signals and determining the pulsar frequency. It will also discuss how dedispersion and the pulsar frequency are critical for predicting multiple characteristics of pulsars and correcting the influence of the Interstellar Medium (ISM).


2021 ◽  
Vol 263 (4) ◽  
pp. 2555-2566
Author(s):  
Roland Sottek ◽  
Thiago Lobato

The Discrete Fourier Transform (DFT) is the standard technique for performing spectral analysis. It is used in the form of the well-known fast implementation (FFT) in almost all areas that deal with signal processing. However, the DFT algorithm has some limitations in terms of its resolution in time and frequency: the higher the time resolution, the lower the frequency resolution, and vice versa. The product of time (analysis duration) and analysis bandwidth (frequency resolution) is a constant. DFT results depend on the analysis window used (type and duration), although the physical signal properties do not change. The High-Resolution Spectral Analysis (HSA) method, published at the ASST '90, considers the window influence through spectral deconvolution and thus leads to a much lower time-bandwidth product, correlating better with human perception. Recently, variants of the HSA have been used for a psychoacoustic standard (roughness). Additionally, HSA is planned for a new model of fluctuation strength. This paper describes the improvements made to the HSA algorithm as well as its robustness against noise, and compares application results for both methods: HSA and DFT.


Author(s):  
Mihail M. Kanarskij ◽  
Julia Yu. Nekrasova ◽  
Ilya V. Borisov ◽  
D. S. Yankevich ◽  
Dmitrij L. Kolesov ◽  
...  

In recent years, EEG spectral analysis has become increasingly popular due to the development of computer technologies. Among the methods of spectral analysis, various variants of the window Fourier transform are most often used, taking into account the non-stationary nature of the EEG signal. In this article, the spectral composition of the sleep EEG of 32 patients with impaired consciousness was studied using a discrete Fourier transform with Windows in the form of elongated spheroidal sequences. The classification of the received gipropischeprom patients with CHF on the dynamics of the spectral composition of the detected correlation characteristic changes in the spectral composition of sleep EEG with the level of consciousness and the etiology of the disease


Author(s):  
André Constantinesco ◽  
Vincent Israel-Jost ◽  
Philippe Choquet

ABSTRACTBackgroundThe weekend effect has been extensively observed for different diseases and countries and recognized as a fact but without obvious causes.ObjectivesIn this paper we first aimed at investigating the existence of a periodicity in the death count due to Covid-19, and second, at opening the discussion concerning the reality of this effect in this particular context.MethodsDaily statistics of deaths due to the Covid-19 pandemic were subjected to a discrete Fourier transform spectral analysis for France and the world, over the periods from March 29 to May 16, 2020 and from January 22 to May 18, 2020 respectively.ResultsIn both cases, a frequency peak of one harmonic corresponding to a period of 7.11 days was observed for France and the world. In France, this weekly frequency corresponds to a decrease in deaths every Sunday, whereas for the world the systematic decrease is shifted on average by 1.5 days and corresponds to Saturday or Friday.ConclusionAt the world scale and for the epidemic period we confirm the existence of a consecutive weekend effect in the context of the Covid-19 pandemic.


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