Corrections to "Short term spectral analysis, synthesis, and modification by discrete Fourier transform"

1977 ◽  
Vol 25 (6) ◽  
pp. 589-589 ◽  
Author(s):  
J. Allen
Keyword(s):  
Spectral Analysis ◽  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Short Term

scholarly journals How can the Fourier Transform be Used in Radio Astronomy to Perform Spectral Analysis of Pulsars

2021 ◽  
Vol 10 (2) ◽  
Author(s):  
Pranesh Kumar ◽  
Arthur Western
Keyword(s):  
Spectral Analysis ◽  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Low Frequency ◽  
Radio Frequency Interference ◽  
Radio Waves ◽  
Folding Algorithm ◽  
Radio Signals ◽  
Multiple Characteristics ◽  
The Fourier Transform

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).

scholarly journals Leak Detection in Waterworks: Comparison Between STFT and FFT with an Overcoming of Limitations

2017 ◽  
Vol 24 (4) ◽  
pp. 631-644 ◽  
Author(s):  
Aimé Lay-Ekuakille ◽  
Giuseppe Griffo ◽  
Paolo Visconti ◽  
Patrizio Primiceri ◽  
Ramiro Velazquez
Keyword(s):  
Spectral Analysis ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Algebraic Approach ◽  
Leak Detection ◽  
Short Term ◽  
Analysis Techniques ◽  
Ill Posed

AbstractDetection of leakages in pipelines is a matter of continuous research because of the basic importance for a waterworks system is finding the point of the pipeline where a leak is located and − in some cases − a nature of the leak. There are specific difficulties in finding leaks by using spectral analysis techniques like FFT (Fast Fourier Transform), STFT (Short Term Fourier Transform), etc. These difficulties arise especially in complicated pipeline configurations, e.g. a zigzag one. This research focuses on the results of a new algorithm based on FFT and comparing them with a developed STFT technique. Even if other techniques are used, they are costly and difficult to be managed. Moreover, a constraint in the leak detection is the pipeline diameter because it influences accuracy of the adopted algorithm. FFT and STFT are not fully adequate for complex configurations dealt with in this paper, since they produce ill-posed problems with an increasing uncertainty. Therefore, an improved Tikhonov technique has been implemented to reinforce FFT and STFT for complex configurations of pipelines. Hence, the proposed algorithm overcomes the aforementioned difficulties due to applying a linear algebraic approach.

High-resolution spectral analysis (HSA) vs. discrete fourier transform (DFT)

2021 ◽  
Vol 263 (4) ◽  
pp. 2555-2566
Author(s):  
Roland Sottek ◽  
Thiago Lobato
Keyword(s):  
Spectral Analysis ◽  
Fourier Transform ◽  
High Resolution ◽  
Discrete Fourier Transform ◽  
Human Perception ◽  
Standard Technique ◽  
Frequency Resolution ◽  
Time Bandwidth Product ◽  
Analysis Window ◽  
Almost All

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.

scholarly journals SPECTRAL EVALUATION OF SLEEP EEG IN PATIENTS WITH CHRONIC DISORDERS OF CONSCIOUSNESS BY MULTI-WINDOW DISCRETE FOURIER TRANSFORM

2020 ◽  
pp. 337-349
Author(s):  
Mihail M. Kanarskij ◽  
Julia Yu. Nekrasova ◽  
Ilya V. Borisov ◽  
D. S. Yankevich ◽  
Dmitrij L. Kolesov ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Spectral Composition ◽  
Sleep Eeg ◽  
Level Of Consciousness ◽  
Spectral Evaluation ◽  
Correlation Characteristic ◽  
Chronic Disorders Of Consciousness

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

scholarly journals Comparative Analysis among Discrete Fourier Transform, K-Means and Artificial Neural Networks Image Processing Techniques Oriented on Quality Control of Assembled Tires

Information ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 257
Author(s):  
Alessandro Massaro ◽  
Giovanni Dipierro ◽  
Emanuele Cannella ◽  
Angelo Maurizio Galiano
Keyword(s):  
Image Processing ◽  
Quality Control ◽  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Short Term Memory ◽  
Short Term ◽  
Image Processing Techniques ◽  
Long Short Term Memory ◽  
Artificial Neural ◽  
Processing Techniques

The present paper discusses a comparative application of image processing techniques, i.e., Discrete Fourier Transform, K-Means clustering and Artificial Neural Network, for the detection of defects in the industrial context of assembled tires. The used Artificial Neural Network technique is based on Long Short-Term Memory and Fully Connected neural networks. The investigations focus on the monitoring and quality control of defects, which may appear on the external surface of tires after being assembled. Those defects are caused from tires which are not properly assembled to their respective metallic wheel rim, generating deformations and scrapes which are not desired. The proposed image processing techniques are applied on raw high-resolution images, which are acquired by in-line imaging and optical instruments. All the described techniques, i.e., Discrete Fourier Transform, K-Means clustering and Long Short-Term Memory, were able to determine defected and acceptable external tire surfaces. The proposed research is taken in the context of an industrial project which focuses on the development of automated quality control and monitoring methodologies, within the field of Industry 4.0 facilities. The image processing techniques are thus meant to be adopted into production processes, giving a strong support to the in-line quality control phase.

scholarly journals Spectral analysis of the daily evolution of deaths due to Covid-19 in France and in the world shows a weekend effect: myth or reality?

2020 ◽  
Author(s):  
André Constantinesco ◽  
Vincent Israel-Jost ◽  
Philippe Choquet
Keyword(s):  
Spectral Analysis ◽  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Weekend Effect ◽  
Frequency Peak ◽  
Epidemic Period ◽  
The World ◽  
Weekly Frequency ◽  
Death Count

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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