Related Experiment Video
Updated: Jul 15, 2025

08:19
Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion
Published on: January 15, 2016
8.9K
A novel algorithm for calculation of Fourier and asymmetric units
1Department of Inorganic Chemistry, Faculty of Natural Sciences, Komensky University, Ilkovicova 6, Bratislava, 84215, Slovak Republic.
Acta Crystallographica. Section A, Foundations and Advances
|September 25, 2023
Summary
A novel method determines asymmetric and Fourier units for all space groups, enhancing fast Fourier transform calculations. This new approach is easily integrated into existing crystallographic software.
Area of Science:
- Crystallography
- Computational Chemistry
- Materials Science
Background:
- Traditional methods for defining asymmetric and Fourier units can be computationally intensive.
- Existing units in the International Tables for Crystallography may not be optimal for modern computational approaches.
Purpose of the Study:
- To introduce a new, efficient method for determining asymmetric and Fourier units applicable to all space groups.
- To enhance the speed and accuracy of fast Fourier transform (FFT) calculations in crystallography.
- To provide a computationally accessible algorithm for crystallographic software.
Main Methods:
- Development of a new algorithm based on plane group properties for defining asymmetric and Fourier units.
- Comparison of the computational efficiency of the new units against those from the International Tables for Crystallography, Vol. A.
- Implementation strategy for integrating the algorithm into existing crystallographic programs.
Main Results:
- The newly derived units significantly improve the efficiency of fast Fourier transform calculations.
- The method provides a consistent and comprehensive approach for all space groups.
- The algorithm requires minimal code for integration, demonstrating its practical utility.
Conclusions:
- The presented method offers a superior alternative for defining asymmetric and Fourier units in crystallographic studies.
- This advancement facilitates faster and more accurate data processing in structural analysis.
- The ease of implementation ensures broad applicability and adoption within the scientific community.
Keywords:
Fortran programFourier unitsasymmetric unit determinationfast Fourier transform calculationsMore Related Videos
Related Concept Videos
Fast Fourier Transform
368
The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
The computational efficiency of the FFT becomes...
368
Properties of Fourier series II
175
Time scaling of signals is a crucial concept in signal processing that affects the Fourier series representation without altering its coefficients. The process modifies the fundamental frequency, thereby changing how the series represents the signal over time. This principle is essential in various applications, including audio and image processing, where signal manipulation is frequent. Understanding function symmetries is fundamental to simplifying the Fourier series.
A function f(t) is...
A function f(t) is...
175
Parseval's Theorem for Fourier transform
1.0K
Parseval's theorem is a fundamental principle in signal processing that enables the calculation of a signal's energy in either the time domain or the frequency domain. This theorem is pivotal in demonstrating energy conservation between these two domains, ensuring that the computed energy value remains consistent regardless of the domain of analysis.
To understand Parseval's theorem, it is essential to first comprehend how signal energy is typically calculated. When considering a...
To understand Parseval's theorem, it is essential to first comprehend how signal energy is typically calculated. When considering a...
1.0K
Trigonometric Fourier series
290
Fourier series is a foundational mathematical technique that decomposes periodic functions into an infinite series of sinusoidal harmonics. This method enables the representation of complex periodic signals as sums of simple sine and cosine functions, facilitating their analysis and interpretation in various fields, including signal processing, acoustics, and electrical engineering.
The trigonometric Fourier series specifically expresses a periodic function with a defined period T using sine...
The trigonometric Fourier series specifically expresses a periodic function with a defined period T using sine...
290
Properties of Fourier Transform II
239
The Fourier Transform (FT) is an essential mathematical tool in signal processing, transforming a time-domain signal into its frequency-domain representation. This transformation elucidates the relationship between time and frequency domains through several properties, each revealing unique aspects of signal behavior.
The Frequency Shifting property of Fourier Transforms highlights that a shift in the frequency domain corresponds to a phase shift in the time domain. Mathematically, if x(t) has...
The Frequency Shifting property of Fourier Transforms highlights that a shift in the frequency domain corresponds to a phase shift in the time domain. Mathematically, if x(t) has...
239
Properties of Fourier series I
330
The Fourier series is a powerful tool in signal processing and communications, allowing periodic signals to be expressed as sums of sine and cosine functions. A foundational property of the Fourier series is linearity. If we consider two periodic signals, their linear combination results in a new signal whose Fourier coefficients are simply the corresponding linear combinations of the original signals' coefficients. This property is crucial in applications like frequency modulation (FM)...
330

