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

214
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,...
214
State Space Representation01:27

State Space Representation

389
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
389
Linear time-invariant Systems01:23

Linear time-invariant Systems

702
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
702
Time and frequency -Domain Interpretation of Phase-lead Control01:24

Time and frequency -Domain Interpretation of Phase-lead Control

330
Phase-lead controllers are commonly used in various control systems to enhance response speed and stability. Adjusting the brightness on a television screen offers a practical example of phase-lead control. When contrast is enhanced, a phase-lead controller is employed. Mathematically, phase-lead control is identified when the first parameter is smaller than the second.
The design of phase-lead control involves the strategic placement of poles and zeros to balance steady-state error and system...
330
RLC Circuit as a Damped Oscillator01:30

RLC Circuit as a Damped Oscillator

1.8K
An RLC circuit combines a resistor, inductor, and capacitor, connected in a series or parallel combination.
Consider a series RLC circuit. Here, the presence of resistance in the circuit leads to energy loss due to joule heating in the resistance. Therefore, the total electromagnetic energy in the circuit is no longer constant and decreases with time. Since the magnitude of charge, current, and potential difference continuously decreases, their oscillations are said to be damped. This is...
1.8K
BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

766
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
766

You might also read

Related Articles

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

Sort by
Same author

A dual-twisted molecular strategy achieves dramatic quantum-yield enhancement in NIR-II AIEgen for high-performance bioimaging.

Biomaterials·2026
Same author

The SQSTM1/<i>p62</i> of Pacific White Shrimp (<i>Litopenaeus vannamei</i>) Is Involved in the Oxidative Stress Induced by Ammonia Exposure.

Animals : an open access journal from MDPI·2026
Same author

A SAUR gene enhances maize drought resilience by promoting silk elongation.

Nature·2026
Same author

Structural and functional characterization of SIRT1 in Litopenaeus vannamei: A regulator of energy metabolism, antioxidant system, autophagy and resistance to bacterial infection.

Fish & shellfish immunology·2026
Same author

Application of Chinese Pre-trained Language Models in Early Detection of Cognitive Impairment: A Comparative Study Based on Spoken Text.

Current Alzheimer research·2026
Same author

First-Principle Study of AlCoCrFeNi High-Entropy Alloys.

Nanomaterials (Basel, Switzerland)·2026

Related Experiment Video

Updated: Nov 27, 2025

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.4K

Complex Modified Projective Synchronization of Fractional-Order Complex-Variable Chaotic System with Unknown Complex

Ruoxun Zhang1, Shiwen Feng1, Shiping Yang2

  • 1College of Primary Education, Xingtai University, Xingtai 054001, China.

Entropy (Basel, Switzerland)
|December 3, 2020
PubMed
Summary

This study introduces a novel method for complex modified projective synchronization (CMPS) in fractional-order complex-variable chaotic systems (FOCCS) with unknown parameters. The new approach simplifies analysis and computation for these complex systems.

Keywords:
complex modified projective synchronization (CMPS)complex-variable chaotic systemunknown complex parameters

More Related Videos

Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.8K
An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

14.0K

Related Experiment Videos

Last Updated: Nov 27, 2025

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.4K
Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.8K
An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

14.0K

Area of Science:

  • Chaos theory
  • Nonlinear dynamics
  • Fractional calculus

Background:

  • Fractional-order complex-variable chaotic systems (FOCCS) exhibit complex dynamics.
  • Achieving synchronization in these systems, especially with unknown parameters, is challenging.
  • Complex modified projective synchronization (CMPS) is a specific type of synchronization with broad applications.

Purpose of the Study:

  • To develop a novel and efficient scheme for CMPS of FOCCS with unknown complex parameters.
  • To provide a new analytical framework for fractional-order complex-valued systems.
  • To reduce the computational complexity associated with analyzing and synchronizing these systems.

Main Methods:

  • Utilizing a complex-variable inequality for analysis.
  • Applying stability theory specific to fractional-order nonlinear systems.
  • Developing a new synchronization scheme tailored for FOCCS.

Main Results:

  • A new scheme for constructing CMPS in FOCCS with unknown complex parameters is successfully presented.
  • The proposed method offers a simplified approach to analyzing fractional-order complex-valued systems.
  • Significant reduction in computational complexity and analysis effort was achieved.

Conclusions:

  • The developed scheme effectively achieves CMPS in FOCCS with unknown complex parameters.
  • The theoretical framework and simulation results validate the proposed synchronization method.
  • This work contributes a more computationally efficient approach to synchronization analysis in complex dynamical systems.