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

Forced Oscillations01:06

Forced Oscillations

7.5K
When an oscillator is forced with a periodic driving force, the motion may seem chaotic. The motions of such oscillators are known as transients. After the transients die out, the oscillator reaches a steady state, where the motion is periodic, and the displacement is determined.
7.5K
Oscillations In An LC Circuit01:30

Oscillations In An LC Circuit

3.0K
An idealized LC circuit of zero resistance can oscillate without any source of emf by shifting the energy stored in the circuit between the electric and magnetic fields. In such an LC circuit, if the capacitor contains a charge q before the switch is closed, then all the energy of the circuit is initially stored in the electric field of the capacitor. This energy is given by
3.0K
Oscillations about an Equilibrium Position01:04

Oscillations about an Equilibrium Position

6.6K
Stability is an important concept in oscillation. If an equilibrium point is stable, a slight disturbance of an object that is initially at the stable equilibrium point will cause the object to oscillate around that point. For an unstable equilibrium point, if the object is disturbed slightly, it will not return to the equilibrium point. There are three conditions for equilibrium points—stable, unstable, and half-stable. A half-stable equilibrium point is also unstable, but is named so...
6.6K
Concept of Resonance and its Characteristics01:19

Concept of Resonance and its Characteristics

6.0K
If a driven oscillator needs to resonate at a specific frequency, then very light damping is required. An example of light damping includes playing piano strings and many other musical instruments. Conversely, to achieve small-amplitude oscillations as in a car's suspension system, heavy damping is required. Heavy damping reduces the amplitude, but the tradeoff is that the system responds at more frequencies. Speed bumps and gravel roads prove that even a car's suspension system is not...
6.0K
Damped Oscillations01:07

Damped Oscillations

6.7K
In the real world, oscillations seldom follow true simple harmonic motion. A system that continues its motion indefinitely without losing its amplitude is termed undamped. However, friction of some sort usually dampens the motion, so it fades away or needs more force to continue. For example, a guitar string stops oscillating a few seconds after being plucked. Similarly, one must continually push a swing to keep a child swinging on a playground.
Although friction and other non-conservative...
6.7K
Multimachine Stability01:25

Multimachine Stability

526
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
526

You might also read

Related Articles

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

Sort by
Same author

Sustaining the chaotic dynamics of the Kuramoto model by adaptable reservoir computer.

Physical review. E·2025
Same author

Measure synchronization transition and its critical behavior in coupled camphor rotors.

Chaos (Woodbury, N.Y.)·2025
Same author

Scalable synchronization cluster in networked chaotic oscillators.

Chaos (Woodbury, N.Y.)·2024
Same author

Folding State within a Hysteresis Loop: Hidden Multistability in Nonlinear Physical Systems.

Physical review letters·2024
Same author

Reconstructing bifurcation diagrams of chaotic circuits with reservoir computing.

Physical review. E·2024
Same author

Breathing cluster in complex neuron-astrocyte networks.

Chaos (Woodbury, N.Y.)·2023
Same journal

Multiscale dynamics of special memristive ion channels in a neural circuit.

Chaos (Woodbury, N.Y.)·2026
Same journal

Symmetry-protected delay spectroscopy in oscillator networks.

Chaos (Woodbury, N.Y.)·2026
Same journal

Mesoscale community organization governs epidemic onset and spread in metapopulations.

Chaos (Woodbury, N.Y.)·2026
Same journal

Topological dependence of viral mutation spread in complex host-interaction networks.

Chaos (Woodbury, N.Y.)·2026
Same journal

Multifractal signatures of Hamiltonian chaos in Hyperion's rotational dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

Exploring mechanisms for reversal of flow in tunicate hearts.

Chaos (Woodbury, N.Y.)·2026
See all related articles

Related Experiment Video

Updated: Jan 6, 2026

Optogenetic Entrainment of Hippocampal Theta Oscillations in Behaving Mice
07:33

Optogenetic Entrainment of Hippocampal Theta Oscillations in Behaving Mice

Published on: June 29, 2018

12.2K

Cluster synchronization in networked nonidentical chaotic oscillators.

Yafeng Wang1, Liang Wang1, Huawei Fan1

  • 1School of Physics and Information Technology, Shaanxi Normal University, Xi'an 710062, China.

Chaos (Woodbury, N.Y.)
|October 3, 2019
PubMed
Summary
This summary is machine-generated.

Stable cluster synchronization is achievable in complex networks with nonidentical chaotic oscillators. Symmetry in network configuration allows synchronization despite parameter mismatch or differing dynamics, crucial for realistic systems.

More Related Videos

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.8K
Basic Caenorhabditis elegans Methods: Synchronization and Observation
11:34

Basic Caenorhabditis elegans Methods: Synchronization and Observation

Published on: June 10, 2012

49.0K

Related Experiment Videos

Last Updated: Jan 6, 2026

Optogenetic Entrainment of Hippocampal Theta Oscillations in Behaving Mice
07:33

Optogenetic Entrainment of Hippocampal Theta Oscillations in Behaving Mice

Published on: June 29, 2018

12.2K
Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.8K
Basic Caenorhabditis elegans Methods: Synchronization and Observation
11:34

Basic Caenorhabditis elegans Methods: Synchronization and Observation

Published on: June 10, 2012

49.0K

Area of Science:

  • Nonlinear dynamics
  • Complex networks
  • Chaos theory

Background:

  • Oscillator synchronization is often hindered by parameter mismatch and differing dynamics in realistic systems.
  • Achieving synchronization in networks of nonidentical oscillators is a significant challenge with broad implications.

Purpose of the Study:

  • To investigate if stable synchronization can be achieved in networked chaotic oscillators with parameter mismatch or different dynamics.
  • To explore the role of network symmetry in enabling synchronization under nonideal conditions.

Main Methods:

  • Modeling networked chaotic oscillators.
  • Utilizing symmetry-based stability analysis.
  • Conducting numerical simulations to validate theoretical predictions.

Main Results:

  • Demonstrated that stable synchronization can be achieved in symmetric complex networks despite parameter mismatch.
  • Identified that cluster synchronization emerges when symmetric nodes share similar parameters or dynamics.
  • Symmetry-based stability analysis accurately predicted the stability of cluster synchronization states.

Conclusions:

  • Network symmetry is a key factor enabling cluster synchronization in systems with nonidentical oscillators.
  • The findings provide insights into the functioning of realistic systems relying on synchronized, nonidentical nonlinear oscillators.
  • This research highlights the interplay between network topology, symmetry, and synchronization phenomena.