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

Properties of Fourier Transform I01:21

Properties of Fourier Transform I

783
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...
783
Transport Number01:31

Transport Number

98
The transport number is the fraction of the total current carried by an ion in an electrolyte solution. It is defined as the ratio of the current carried by a specific ion to the total current flowing through the solution. The transport number, t, is central to understanding ionic mobility, which describes how fast an ion moves under the influence of an electric field. This link connects the physical behavior of ions in solution to the chemical processes that occur during electrochemical...
98
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

825
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
825
Properties of Fourier Transform II01:24

Properties of Fourier Transform II

890
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...
890
Parseval's Theorem for Fourier transform01:15

Parseval's Theorem for Fourier transform

2.4K
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...
2.4K
Frequency Response of a Circuit01:20

Frequency Response of a Circuit

933
Inductive circuits present intriguing challenges in electrical engineering, particularly during the transition from the time domain to the frequency domain. This transformation involves converting inductors into impedances and utilizing phasor representation.
The transfer function is pivotal in characterizing how these circuits react to various frequencies, facilitating a profound understanding of their behavior. An essential parameter is the time constant, signifying the...
933

You might also read

Related Articles

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

Sort by
Same author

Inhibition of ADSS2-mediated de novo AMP biosynthesis re-sensitizes acute myeloid leukemia to BH3 mimetics.

Nature cancer·2026
Same author

Tumor mitochondrial respiration rather than glycolytic activity predicts recurrence in colorectal cancer: an ex vivo bioenergetic profiling study.

BMC gastroenterology·2026
Same author

Spin-Selective Oxygen Evolution in Chiral Molecule-Intercalated Layered Double Hydroxides.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Interleukin-4-producing type 2 innate lymphoid cells in the lymph node promote proallergic Tfh13 cell differentiation.

Immunity·2026
Same author

Graphene-Scaffolded Ultrathin Perovskite Nanocrystal Films for Amplifying Energy Localization via Dual-Mode Nonhybridizing Quasi-BICs.

Nano letters·2026
Same author

Probing the effective mass and fermi velocity of charges by momentum-resolved electron energy loss spectroscopy.

Microscopy (Oxford, England)·2026

Related Experiment Video

Updated: Mar 21, 2026

Deriving the Time Course of Glutamate Clearance with a Deconvolution Analysis of Astrocytic Transporter Currents
09:42

Deriving the Time Course of Glutamate Clearance with a Deconvolution Analysis of Astrocytic Transporter Currents

Published on: August 7, 2013

10.9K

Phase retrieval by using the transport-of-intensity equation with Hilbert transform.

Wei-Shuo Li, Chun-Wei Chen, Kuo-Feng Lin

    Optics Letters
    |May 19, 2016
    PubMed
    Summary
    This summary is machine-generated.

    The Hilbert transform method offers superior phase recovery for imaging periodic and aperiodic structures. This non-iterative technique provides smoother phase images with enhanced details compared to conventional methods.

    More Related Videos

    Real-time Iontophoresis with Tetramethylammonium to Quantify Volume Fraction and Tortuosity of Brain Extracellular Space
    10:45

    Real-time Iontophoresis with Tetramethylammonium to Quantify Volume Fraction and Tortuosity of Brain Extracellular Space

    Published on: July 24, 2017

    12.9K
    A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors
    11:15

    A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

    Published on: May 30, 2016

    26.4K

    Related Experiment Videos

    Last Updated: Mar 21, 2026

    Deriving the Time Course of Glutamate Clearance with a Deconvolution Analysis of Astrocytic Transporter Currents
    09:42

    Deriving the Time Course of Glutamate Clearance with a Deconvolution Analysis of Astrocytic Transporter Currents

    Published on: August 7, 2013

    10.9K
    Real-time Iontophoresis with Tetramethylammonium to Quantify Volume Fraction and Tortuosity of Brain Extracellular Space
    10:45

    Real-time Iontophoresis with Tetramethylammonium to Quantify Volume Fraction and Tortuosity of Brain Extracellular Space

    Published on: July 24, 2017

    12.9K
    A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors
    11:15

    A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

    Published on: May 30, 2016

    26.4K

    Area of Science:

    • Optics
    • Image Processing
    • Materials Science

    Background:

    • Phase recovery is crucial for analyzing transparent materials.
    • Traditional methods like interferometry are complex and iterative.
    • Transport-of-Intensity Equation (TIE) offers a non-interferometric approach.

    Purpose of the Study:

    • To compare different methods for solving the TIE for phase recovery.
    • To evaluate the effectiveness of the Hilbert transform method for phase imaging.
    • To assess the quantitative phase mapping capabilities for various sample types.

    Main Methods:

    • Solving the Transport-of-Intensity Equation (TIE) using conventional, one partial derivative, and Hilbert transform methods.
    • Applying these methods to both periodic and aperiodic samples.
    • Comparing the resulting phase images with those obtained from optical and atomic force microscopy.

    Main Results:

    • The Hilbert transform method yields smoother phase images with enhanced edge details and fine structures.
    • This method demonstrates superior performance over conventional TIE approaches.
    • Quantitative phase mapping of periodic and aperiodic structures was achieved.

    Conclusions:

    • The Hilbert transform method is a powerful, non-iterative technique for phase recovery.
    • It offers significant advantages in image quality and quantitative analysis.
    • This method is suitable for diverse sample types in various scientific fields.