Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Fast Fourier Transform01:10

Fast Fourier Transform

952
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)log⁡2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
952
Properties of Fourier Transform I01:21

Properties of Fourier Transform I

671
The application of Fourier Transform properties in radio broadcasting is multifaceted, enabling significant advancements in the way signals are transmitted and received. Key areas where these properties are utilized include simultaneous multi-channel transmission, audio clip speed adjustments, live broadcast delays for different time zones, audio frequency adjustments, and signal demodulation.
In radio broadcasting, multiple audio signals often need to be transmitted simultaneously. The Fourier...
671
Properties of Fourier Transform II01:24

Properties of Fourier Transform II

782
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...
782
Discrete Fourier Transform01:15

Discrete Fourier Transform

913
The Discrete Fourier Transform (DFT) is a fundamental tool in signal processing, extending the discrete-time Fourier transform by evaluating discrete signals at uniformly spaced frequency intervals. This transformation converts a finite sequence of time-domain samples into frequency components, each representing complex sinusoids ordered by frequency. The DFT translates these sequences into the frequency domain, effectively indicating the magnitude and phase of each frequency component present...
913
Basic signals of Fourier Transform01:07

Basic signals of Fourier Transform

955
The Fourier Transform is a pivotal mathematical tool in signal processing, enabling the transformation of time-domain signals into their frequency-domain representations. Among the numerous elements within this domain, certain functions like the sinc function, delta function, and exponential signals hold significant importance due to their unique properties and implications.
The sinc function, defined as sinc(x) = sin(πx)/(πx), is particularly notable for its symmetry and behavior at...
955
Continuous -time Fourier Transform01:11

Continuous -time Fourier Transform

918
The Fourier series is instrumental in representing periodic functions, offering a powerful method to decompose such functions into a sum of sinusoids. This technique, however, necessitates modification when applied to nonperiodic functions. Consider a pulse-train waveform consisting of a series of rectangular pulses. When these pulses have a finite period, they can be accurately represented by a Fourier series. Yet, as the period approaches infinity, resulting in a single, isolated pulse, the...
918

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Amlodipine Besylate-Folic Acid demonstrates superior efficacy to Enalapril Maleate-Folic Acid in treating H-type hypertension.

American journal of translational research·2026
Same author

Fast registration method for sequential star images.

Applied optics·2023
Same author

Fully connected aperture array design of the segmented planar imaging system.

Optics letters·2022
Same author

Single photonic integrated circuit imaging system with a 2D lens array arrangement.

Optics express·2022
Same author

Star Identification Based on Multilayer Voting Algorithm for Star Sensors.

Sensors (Basel, Switzerland)·2021
Same author

System design of an optical interferometer based on compressive sensing: an update.

Optics express·2020
Same journal

Multifunctional reconfigurable terahertz metasurface based on vanadium dioxide phase transition: achieving broadband absorption and efficient polarization conversion.

Applied optics·2026
Same journal

High-Q-factor electromagnetically induced transparency utilizing quasi-bound states in the continuum in an all-dielectric terahertz metasurface.

Applied optics·2026
Same journal

Automated stitching interferometry for high-precision metrology of X-ray mirrors.

Applied optics·2026
Same journal

Experimental demonstration of an approach to designing a metal-dielectric DBR resonant cavity structure.

Applied optics·2026
Same journal

High-precision wavefront reconstruction from a single-shot interferogram using a physics-driven hybrid feature calibration network.

Applied optics·2026
Same journal

Ultra-high-Q Fano resonance based on coupled topological corner states in Kagome photonic crystals.

Applied optics·2026
See all related articles

Related Experiment Video

Updated: Feb 6, 2026

A Multimodal Wide-Field Fourier-Transform Raman Microscope
06:48

A Multimodal Wide-Field Fourier-Transform Raman Microscope

Published on: December 30, 2025

402

Spectrum reconstruction in Fourier transform imaging spectroscopy based on high-performance parallel computing.

Weikang Zhang, Desheng Wen, Zongxi Song

    Applied Optics
    |August 18, 2018
    PubMed
    Summary
    This summary is machine-generated.

    Parallel processing algorithms accelerate spectrum reconstruction in Fourier transform imaging spectroscopy. Graphics processing unit (GPU) acceleration significantly reduces runtime for large datasets, improving efficiency for spectral data analysis.

    More Related Videos

    Fourier-Based Diffraction Analysis of Live Caenorhabditis elegans
    08:24

    Fourier-Based Diffraction Analysis of Live Caenorhabditis elegans

    Published on: September 13, 2017

    8.3K
    Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy
    10:03

    Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy

    Published on: June 27, 2014

    18.4K

    Related Experiment Videos

    Last Updated: Feb 6, 2026

    A Multimodal Wide-Field Fourier-Transform Raman Microscope
    06:48

    A Multimodal Wide-Field Fourier-Transform Raman Microscope

    Published on: December 30, 2025

    402
    Fourier-Based Diffraction Analysis of Live Caenorhabditis elegans
    08:24

    Fourier-Based Diffraction Analysis of Live Caenorhabditis elegans

    Published on: September 13, 2017

    8.3K
    Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy
    10:03

    Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy

    Published on: June 27, 2014

    18.4K

    Area of Science:

    • Spectroscopy
    • Computational Imaging
    • High-Performance Computing

    Background:

    • Fourier transform imaging spectroscopy generates massive interference data.
    • Traditional algorithms are inefficient and time-consuming for large datasets.
    • Rapid spectral data formation is crucial for research and economic applications.

    Purpose of the Study:

    • To propose parallel-processing algorithms for spectrum reconstruction.
    • To leverage high-performance parallel computing, specifically graphics processing units (GPUs), for enhanced efficiency.
    • To reduce operation time in processing interference data.

    Main Methods:

    • Development of parallel-processing algorithms tailored for GPUs.
    • Implementation of these algorithms for spectrum reconstruction in Fourier transform imaging spectroscopy.
    • Comparison with traditional algorithms processed on the central processing unit (CPU).

    Main Results:

    • Significant reduction in runtime from 1.144 ms to 0.332 ms using parallel GPU algorithms.
    • Demonstrated advantage of the parallel-processing mechanism on GPUs for large-scale interference data.
    • Improved efficiency and reduced processing time compared to traditional CPU-based methods.

    Conclusions:

    • Parallel-processing algorithms on GPUs offer a substantial improvement for spectrum reconstruction.
    • GPU acceleration is highly effective for handling the large data volumes in Fourier transform imaging spectroscopy.
    • The proposed method provides a faster and more efficient approach to spectral data processing.