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

Gaussian Elimination: Problem Solving01:30

Gaussian Elimination: Problem Solving

266
Systems of linear equations in several variables are pivotal in modeling complex scenarios involving multiple unknowns and constraints. Such systems are widely used in various fields to represent relationships where several conditions must be simultaneously satisfied. Each variable in the system corresponds to an unknown quantity, while each equation imposes a linear constraint, leading to a structured approach for analyzing and solving real-world problems.A system of three equations with three...
266
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

5.4K
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...
5.4K
Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

20.4K
It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...
20.4K
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

9.7K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
9.7K
Quadratic Models01:23

Quadratic Models

285
Quadratic models are mathematical representations used to describe relationships in which the rate of change changes at a constant rate. These models appear in a wide variety of natural and engineered systems, especially those involving motion, forces, and optimization. One common application is analyzing the vertical motion of objects influenced by gravity, such as a ball thrown into the air.In such scenarios, the object's height changes over time in a curved pattern, rising to a maximum point...
285
Compacting Factor test01:22

Compacting Factor test

676
The compacting factor test is a method used to assess the workability of concrete. It is  especially suitable for concrete mixes containing aggregates up to one and a half inches in size. This test involves specialized equipment consisting of two truncated cone-shaped hoppers and a cylinder, all with polished interior surfaces to minimize friction.
The procedure begins by placing concrete into the upper hopper without any compaction. Once filled, the bottom door of this hopper is opened,...
676

You might also read

Related Articles

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

Sort by
Same author

The Laminar Organization of a Decision Circuit in Orbitofrontal Cortex is Agnostic to the Variable Encoding Scheme.

bioRxiv : the preprint server for biology·2026
Same author

An optimal pairwise merge algorithm improves the quality and consistency of nonnegative matrix factorization.

IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society·2025
Same author

Laminar Architecture of a Decision Circuit in Orbitofrontal Cortex.

bioRxiv : the preprint server for biology·2025
Same author

The representation of decision variables in orbitofrontal cortex is longitudinally stable.

Cell reports·2024
Same author

STARDUST: A pipeline for the unbiased analysis of astrocyte regional calcium dynamics.

STAR protocols·2024
Same author

The Representation of Decision Variables in Orbitofrontal Cortex is Longitudinally Stable.

bioRxiv : the preprint server for biology·2024
Same journal

Topological skeleton analysis for network-based shape representation in biology and beyond.

iScience·2026
Same journal

Condition-specific neural signatures of reactivation during post-retrieval rest: An EEG study.

iScience·2026
Same journal

Multi-chaotic signal identification employing a causal cross-correlation neural network.

iScience·2026
Same journal

Repeated insertions at positions 261-280 in KPC-2 highlight a ceftazidime-avibactam resistance hotspot.

iScience·2026
Same journal

ROS inhibits microtubule dynamics and cell growth heterogeneity during Arabidopsis sepal morphogenesis.

iScience·2026
Same journal

Type 1 diabetes alters early macrophage-<i>Mycobacterium tuberculosis</i> transcriptional coordination during infection.

iScience·2026
See all related articles

Related Experiment Video

Updated: Mar 19, 2026

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

18.5K

Recovering missing features in nonnegative matrix factorization via generalized singular value decomposition.

Youdong Guo1, Timothy E Holy1,2

  • 1Department of Neuroscience, Washington University in St. Louis, St. Louis, MO, USA.

Iscience
|March 18, 2026
PubMed
Summary
This summary is machine-generated.

Generalized Singular Value Decomposition-Nonnegative Matrix Factorization (GSVD-NMF) enhances source separation by recovering missing components. This interactive method improves Nonnegative Matrix Factorization (NMF) results and is more efficient than rerunning analyses.

Keywords:
Applied sciencesNetwork

More Related Videos

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.4K
Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

2.2K

Related Experiment Videos

Last Updated: Mar 19, 2026

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

18.5K
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.4K
Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

2.2K

Area of Science:

  • Data Analysis
  • Matrix Factorization
  • Signal Processing

Background:

  • Nonnegative Matrix Factorization (NMF) is crucial for source separation but requires pre-defined ranks.
  • Current NMF methods necessitate re-computation with different ranks for unsatisfactory results.

Purpose of the Study:

  • Introduce GSVD-NMF, an interactive method to improve NMF by addressing under-complete results.
  • Enhance NMF interactivity and efficiency in component recovery.

Main Methods:

  • Propose new components using Generalized Singular Value Decomposition (GSVD) to correct NMF discrepancies.
  • Integrate GSVD-NMF with existing NMF algorithms.
  • Utilize relaxed convergence tolerance for under-complete NMF computation.

Main Results:

  • GSVD-NMF effectively recovers missing components in under-complete NMF scenarios.
  • Recovered NMF solutions frequently achieve better local optima.
  • GSVD-NMF demonstrates compatibility with various NMF algorithms.
  • Component augmentation is more efficient than rerunning NMF.
  • Relaxed convergence tolerance reduces runtime while maintaining accuracy.

Conclusions:

  • GSVD-NMF offers an efficient and interactive approach to enhance NMF.
  • The method improves component recovery and solution quality in source separation tasks.
  • GSVD-NMF provides a viable alternative to iterative NMF re-computation.