scholarly journals CCD PHOTOMETRY AND EVOLUTIONARY STATUS OF THE PULSATING VARIABLE CSS J051053.0+071722

2020 ◽  
Vol 56 (1) ◽  
pp. 129-138
Author(s):  
K. B. Alton
Keyword(s):  
Fourier Transformation ◽  
System Analysis ◽  
Type System ◽  
Physical Nature ◽  
High Amplitude ◽  
Photometric Data ◽  
Discrete Fourier Transformation ◽  
Evolutionary Status ◽  
Ccd Photometry ◽  
Precise Time

Multi-color (BV I_c ) CCD-derived photometric data were acquired for CSSJ051053.0+071722, a pulsating variable classified as a high amplitude δ Scuti-type system. Analysis of precise time-series lightcurve data was accomplished using discrete Fourier transformation which revealed a mean fundamental mode (f_0 ) of oscillation at 14.5097 ±0.0001 d^−1 along with two other partial harmonics (2f_0 and 4f_0 ). No other statistically significant frequency shared by all bandpasses was resolved following successive pre-whitening of each residual signal. Except for 36 new times-of-maximum light produced from the present study, no other values were found in the literature; therefore, potential secular period changes could not be evaluated. The evolutionary status, age and physical nature of CSS J051053.0+071722 were investigated using the PAdova & TRieste Stellar Evolution Code for generating stellar tracks and isochrones.

Generation of Wave-Field Time Histories by the Modulated Discrete Fourier Transformation

2003 ◽  
Author(s):  
Yousun Li
Keyword(s):  
Wave Field ◽  
Fourier Transformation ◽  
Time Instant ◽  
Discrete Fourier Transformation ◽  
Fast Fourier Transformation ◽  
Structural Members ◽  
Random Waves ◽  
Offshore Structure ◽  
Time Histories ◽  
The Time Domain

In the time domain simulation of the response of an offshore structure under random waves, the time histories of the wave field should be generated as the input to the dynamic equations. Herein the wave field is the wave surface elevation, the water particle velocities and accelerations at structural members. The generated time histories should be able to match the given wave-field spectral descriptions, to trace the structural member motions if it is a compliant offshore structure, and be numerically efficient. Most frequently used generation methods are the direct summation of a limited number of cosine functions, the Fast Fourier Transformation, and the digital filtering model. However, none of them can really satisfy all the above requirements. A novel technique, called the Modulated Discrete Fourier Transformation, has been developed. Under this method, the wave time histories at each time instant is a summation of a few time-varying complex functions. The simulated time histories have continuous spectral density functions, and the motions of the structural members are well included. This method seems to be superior to all the conventional methods in terms of the above mentioned three requirements.

scholarly journals Comparison of delayless digital filtering algorithms and their application to multi-sensor signal processing

2018 ◽  
Vol 41 (8) ◽  
pp. 2338-2351 ◽  
Author(s):  
Anna Swider ◽  
Eilif Pedersen
Keyword(s):  
Signal Processing ◽  
Fourier Transformation ◽  
Filter Design ◽  
Real Life ◽  
Digital Filtering ◽  
Data Preprocessing ◽  
Sensor Data ◽  
Discrete Fourier Transformation ◽  
Filtering Algorithms ◽  
Multiple Sensors

In the phase of industry digitalization, data are collected from many sensors and signal processing techniques play a crucial role. Data preprocessing is a fundamental step in the analysis of measurements, and a first step before applying machine learning. To reduce the influence of distortions from signals, selective digital filtering is applied to minimize or remove unwanted components. Standard software and hardware digital filtering algorithms introduce a delay, which has to be compensated for to avoid destroying signal associations. The delay from filtering becomes more crucial when the analysis involves measurements from multiple sensors, therefore in this paper we provide an overview and comparison of existing digital filtering methods with an application based on real-life marine examples. In addition, the design of special-purpose filters is a complex process and for preprocessing data from many sources, the application of digital filtering in the time domain can have a high numerical cost. For this reason we describe discrete Fourier transformation digital filtering as a tool for efficient sensor data preprocessing, which does not introduce a time delay and has low numerical cost. The discrete Fourier transformation digital filtering has a simpler implementation and does not require expert-level filter design knowledge, which is beneficial for practitioners from various disciplines. Finally, we exemplify and show the application of the methods on real signals from marine systems.

scholarly journals Multiplication of Polynomials using Discrete Fourier Transformation

2006 ◽  
Vol 14 (4) ◽  
pp. 121-128
Author(s):  
Krzysztof Treyderowski ◽  
Christoph Schwarzweller
Keyword(s):  
Fourier Transformation ◽  
Discrete Fourier Transformation ◽  
Vandermonde Matrices ◽  
Univariate Polynomials

Multiplication of Polynomials using Discrete Fourier Transformation In this article we define the Discrete Fourier Transformation for univariate polynomials and show that multiplication of polynomials can be carried out by two Fourier Transformations with a vector multiplication in-between. Our proof follows the standard one found in the literature and uses Vandermonde matrices, see e.g. [27].

scholarly journals Bulge δ Scuti stars in the MACHO database

1997 ◽  
Vol 189 ◽  
pp. 293-298
Author(s):  
D. Minniti ◽  
C. Alcock ◽  
D.R. Alves ◽  
T.S. Axelrod ◽  
A.C. Becker ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
High Amplitude ◽  
Light Curves ◽  
Evolutionary Status ◽  
Absolute Magnitudes ◽  
Scuti Stars ◽  
Δ Scuti Stars

We describe the search for δ Scuti stars in the MACHO database of bulge fields. Concentrating on a sample of high amplitude δ Scutis, we examine the light curves and pulsation modes. We also discuss their spatial distribution and evolutionary status using mean colors and absolute magnitudes.

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