Jove
Visualize
Contact Us

Related Concept Videos

Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

13.9K
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...
13.9K
Vector Representation of Complex Numbers01:16

Vector Representation of Complex Numbers

122
Complex numbers, represented in Cartesian coordinates, can also be visualized as vectors. These vectors can be expressed in polar form, emphasizing their magnitude and angle. When a complex number is input into a function, the output is another complex number, highlighting the function's zero point from which the vector representation can originate.
Consider a function defined as the product of the complex factors in the numerator divided by the product of the complex factors in the...
122
Vector Operations01:20

Vector Operations

1.3K
Vectors are physical quantities that have both magnitude and direction. The vector operations include addition, subtraction, and scalar multiplication.
A vector multiplied by a scalar value is called scalar multiplication. The result obtained is a new vector with a different magnitude. If the scalar is positive, the direction of the vector remains the same, but if it is negative, the direction of the vector is reversed. For example, the product of the mass and velocity yields the momentum.
1.3K
Introduction to Scalars01:21

Introduction to Scalars

14.5K
Many familiar physical quantities can be specified completely by giving a single number and the appropriate unit. For example, "a class period lasts 50 min," or "the gas tank in my car holds 65 L," or "the distance between the two posts is 100 m." A physical quantity that can be specified completely in this manner is called a scalar quantity. The word "scalar" is a synonym for "number." Time, mass, distance, length, volume,...
14.5K
Scalar and Vectors01:22

Scalar and Vectors

1.2K
In mechanics, commonly used terms like force, speed, velocity, and work can be classified as either scalar or vector quantities. A scalar is a physical quantity that can be described by its magnitude alone and does not require any directional components. Examples of scalar quantities are mass, area, and length.
Scalar quantities with the same physical units can be added or subtracted according to the usual algebra rules for numbers. For example, a class ending 10 min earlier than 50 min lasts...
1.2K
Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

12.1K
Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...
12.1K

You might also read

Related Articles

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

Sort by
Same author

Determination of sexual dimorphism with CBCT images of the frontal sinus using a predictive formula and an artificial neural network.

Journal of applied oral science : revista FOB·2025
Same author

User-Centric Cell-Free Massive Multiple-Input-Multiple-Output System with Noisy Channel Gain Estimation and Line of Sight: A Beckmann Distribution Approach.

Entropy (Basel, Switzerland)·2025
Same author

Machine Learning and Graph Signal Processing Applied to Healthcare: A Review.

Bioengineering (Basel, Switzerland)·2024
Same author

Automatic Classification System for Periapical Lesions in Cone-Beam Computed Tomography.

Sensors (Basel, Switzerland)·2022
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 Experiment Video

Updated: Jun 27, 2025

SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware
08:13

SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware

Published on: December 25, 2017

8.2K

On the Initialization of Swarm Intelligence Algorithms for Vector Quantization Codebook Design.

Verusca Severo1, Felipe B S Ferreira2, Rodrigo Spencer1

  • 1Polytechnic School of Pernambuco, University of Pernambuco, Recife 50720-001, Brazil.

Sensors (Basel, Switzerland)
|April 27, 2024
PubMed
Summary

Novel initialization strategies significantly enhance Vector Quantization (VQ) codebook design. These methods improve image reconstruction quality and reduce codebook design time compared to random initialization.

Keywords:
image compressioninitializationswarm intelligencevector quantization

More Related Videos

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

541
Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification
07:47

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification

Published on: February 14, 2018

11.2K

Related Experiment Videos

Last Updated: Jun 27, 2025

SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware
08:13

SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware

Published on: December 25, 2017

8.2K
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

541
Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification
07:47

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification

Published on: February 14, 2018

11.2K

Area of Science:

  • Computer Science
  • Signal Processing
  • Artificial Intelligence

Background:

  • Vector Quantization (VQ) is crucial for signal processing, particularly in image compression.
  • The Linde-Buzo-Gray (LBG) algorithm is a standard for VQ codebook design, but its performance heavily relies on initial codebook selection.
  • Random initialization is common but often suboptimal for VQ codebook quality and convergence speed.

Purpose of the Study:

  • To evaluate the impact of novel initialization strategies on swarm intelligence-based VQ codebook design algorithms.
  • To assess the effectiveness of these strategies in improving codebook quality and convergence speed.
  • To compare combined initialization techniques against traditional random initialization.

Main Methods:

  • Investigated nine initialization strategies combining literature-based and random vector selection for VQ codebooks.
  • Applied these strategies to modified Firefly Algorithm-LBG (M-FA-LBG), Particle Swarm Optimization-LBG (M-PSO-LBG), and Fish School Search-LBG (M-FSS-LBG) algorithms, including accelerated versions.
  • Evaluated codebook quality using Peak Signal-to-Noise Ratio (PSNR) for reconstructed images and convergence speed by iteration count.

Main Results:

  • Proposed initialization strategies demonstrated significant improvements over random initialization.
  • Achieved gains up to 4.43 dB in PSNR for the 'Clock' image using M-PSO-LBG with 512 codebooks.
  • Reported codebook design time savings of up to 67.05% for the 'Clock' image with M-FF-LBGa (accelerated Firefly Algorithm-LBG) and 512 codebooks.

Conclusions:

  • Initialization strategies offer a promising approach to enhance VQ codebook design.
  • Combining different initialization techniques can lead to superior codebook quality and faster convergence.
  • The findings support the adoption of these advanced initialization methods for swarm intelligence-based VQ algorithms.