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

Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

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 sampling...
Even and Odd Signals01:17

Even and Odd Signals

An even signal, whether in continuous-time or discrete-time, is defined by its symmetry with its time-reversed version. Mathematically, this is represented as
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
Aliasing01:18

Aliasing

Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original signal...
Mason's Rule01:20

Mason's Rule

Mason's rule is a powerful tool in control systems and signal processing. It simplifies the calculation of transfer functions from signal-flow graphs. This method leverages various elements, including loop gains, forward-path gains, and non-touching loops, to determine the transfer function efficiently.
Loop gain is determined by identifying and tracing a path from a node back to itself. This involves computing the product of branch gains along the loop. Each loop's gain is crucial for further...
Deconvolution01:20

Deconvolution

Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...

You might also read

Related Articles

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

Sort by
Same author

Publisher Correction: Signal transmission through elements of the cytoskeleton form an optimized information network in eukaryotic cells.

Scientific reports·2019
Same author

Signal transmission through elements of the cytoskeleton form an optimized information network in eukaryotic cells.

Scientific reports·2019
Same author

Minimum entropy-neural network approach to turbulent-image reconstruction.

Applied optics·2010
Same author

Bayesian cross-entropy reconstruction of complex images.

Applied optics·2010
Same author

Multiple-filter approach to phase retrieval from modulus data.

Applied optics·2010
Same author

Integral logarithmic transform: theory and applications.

Applied optics·2010

Related Experiment Video

Updated: Jun 7, 2026

Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy
07:29

Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy

Published on: May 27, 2020

Reconstruction of complex signals using minimum Rényi information.

B R Frieden, A T Bajkova

    Applied Optics
    |November 6, 2010
    PubMed
    Summary

    Rényi

    Area of Science:

    • Image reconstruction
    • Information theory
    • Signal processing

    Background:

    • Information divergence quantifies distance between probability distributions.
    • Amari's α-divergences offer desirable properties like convexity.
    • Rényi's information Dα is a convex α-divergence.

    Purpose of the Study:

    • To apply Rényi's information Dα for image reconstruction.
    • To leverage convexity for efficient minimization.
    • To reconstruct complex images, such as in inverse synthetic-aperture radar imaging.

    Main Methods:

    • Minimizing Dα to achieve minimum distance between images.
    • Replacing probabilities with complex amplitudes in the Rényi form.
    • Constructing a bias image from a smoothed linear Fourier reconstruction.

    More Related Videos

    Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
    09:23

    Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

    Published on: August 16, 2017

    Related Experiment Videos

    Last Updated: Jun 7, 2026

    Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy
    07:29

    Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy

    Published on: May 27, 2020

    Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
    09:23

    Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

    Published on: August 16, 2017

    Main Results:

    • The Rényi reconstruction approach enables superresolution in low-noise scenarios.
    • Higher fidelity is achieved compared to linear reconstructions in noisy cases.
    • Simulated data demonstrated the effectiveness of the method.

    Conclusions:

    • Rényi's information Dα provides an effective method for image reconstruction.
    • The approach offers advantages in both low-noise (superresolution) and high-noise (fidelity) conditions.
    • This technique is valuable for complex image reconstruction tasks.