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

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

275
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
275
Properties of the z-Transform II01:16

Properties of the z-Transform II

332
The property of Accumulation in signal processing is derived by analyzing the accumulated sum of a discrete-time signal and using the time-shifting property to determine its z-transform. This principle reveals that the z-transform of the summed signal is related to the z-transform of the original signal by a multiplicative factor.
Moreover, the convolution property indicates that the convolution of two signals in the time domain corresponds to the product of their z-transforms in the frequency...
332
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

306
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
306
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

4.5K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
4.5K
Properties of the z-Transform I01:17

Properties of the z-Transform I

554
The z-transform is a fundamental tool in digital signal processing, enabling the analysis of discrete-time systems through its various properties. It is an invaluable tool for analyzing discrete-time systems, offering a range of properties that simplify complex signal manipulations. One fundamental property is linearity. For any two discrete-time signals, the z-transform of their linear combination equals the same linear combination of their individual z-transforms. This property is essential...
554
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

800
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
800

You might also read

Related Articles

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

Sort by
Same author

Scanpath Prediction in Panoramic Videos Via Expected Code Length Minimization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Self-Supervised AI-Generated Image Detection: A Camera Metadata Perspective.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

A Perceptually Optimized and Self-Calibrated Tone Mapping Operator.

IEEE transactions on visualization and computer graphics·2025
Same author

Comparison of Endoscopic Unilateral Laminectomy for Bilateral Decompression (Endo-ULBD) and Posterior Lumbar Interbody Fusion (PLIF) in Managing Multi-Segmental Lumbar Spinal Stenosis: Technique and Early Outcomes.

Orthopaedic surgery·2025
Same author

Application of Interpretable Machine Learning Algorithm to Predict Lymph Node Metastasis in Cutaneous Malignant Melanoma.

Dermatology (Basel, Switzerland)·2025
Same author

FTO-mediated m6A Demethylation of OTUB1 stabilizes SLC7A11 to alleviate Ferroptosis in cerebral ischemia/reperfusion injury.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association·2025

Related Experiment Video

Updated: Dec 22, 2025

Characterization of Anisotropic Leaky Mode Modulators for Holovideo
09:36

Characterization of Anisotropic Leaky Mode Modulators for Holovideo

Published on: March 19, 2016

8.2K

Characterizing Generalized Rate-Distortion Performance of Video Coding: An Eigen Analysis Approach.

Zhengfang Duanmu, Wentao Liu, Zhuoran Li

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |May 2, 2020
    PubMed
    Summary
    This summary is machine-generated.

    This study models the generalized rate-distortion (GRD) trade-off in video compression. A novel eigen GRD method accurately estimates video quality from minimal data, outperforming existing techniques.

    More Related Videos

    Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
    13:44

    Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

    Published on: August 30, 2013

    43.5K
    Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves
    06:26

    Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves

    Published on: January 12, 2024

    672

    Related Experiment Videos

    Last Updated: Dec 22, 2025

    Characterization of Anisotropic Leaky Mode Modulators for Holovideo
    09:36

    Characterization of Anisotropic Leaky Mode Modulators for Holovideo

    Published on: March 19, 2016

    8.2K
    Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
    13:44

    Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

    Published on: August 30, 2013

    43.5K
    Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves
    06:26

    Stereo-Imaging System DLT Calibration to Capture 3D In Situ Displacements of Stretched Peripheral Nerves

    Published on: January 12, 2024

    672

    Area of Science:

    • Computer Vision
    • Information Theory
    • Signal Processing

    Background:

    • Rate-distortion (RD) theory is fundamental to lossy data compression.
    • Modeling the generalized RD (GRD) trade-off is crucial for optimizing video encoding profiles like bitrate and spatial resolution.

    Purpose of the Study:

    • To develop a computational model for the GRD function.
    • To create an efficient method for estimating GRD parameters from sparse data.
    • To improve the accuracy and efficiency of RD estimation in video compression.

    Main Methods:

    • Defined the theoretical functional space W of the GRD function using mathematical properties, identifying it as a convex set in a Hilbert space.
    • Developed a computational model for GRD functions and a parameter estimation method using sparse measurements.
    • Collected a large-scale database of real-world GRD functions, revealing a low-dimensional subspace within W.
    • Proposed a low-parameter eigen GRD method combining the GRD reconstruction framework and the learned low-dimensional space.

    Main Results:

    • The GRD functions were found to reside in a low-dimensional subspace of W.
    • The eigen GRD method accurately estimates GRD functions from few queries.
    • The learned GRD method significantly outperformed state-of-the-art empirical RD estimation methods in accuracy and efficiency.

    Conclusions:

    • The proposed eigen GRD method offers a significant advancement in modeling and estimating the generalized rate-distortion trade-off for video compression.
    • The findings demonstrate the potential of the model for applications such as video codec comparison.