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Related Concept Videos

BIBO stability of continuous and discrete -time systems01:24

BIBO stability of continuous and discrete -time systems

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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....
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Generation and Coherent Control of Pulsed Quantum Frequency Combs
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RBFNN-PSO Intelligent Synchronisation Method for Sprott B Chaotic Systems with External Noise and Its Application in

Yanpeng Zhang1,2, Jian Zeng1, Wenhao Yan1

  • 1Electrical Engineering College, Heilongjiang University, Harbin 150080, China.

Entropy (Basel, Switzerland)
|October 25, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel RBFNN-PSO synchronization method for the Sprott B chaotic system, effectively combating external noise for secure communication. The method is then applied to image encryption, demonstrating robust performance.

Keywords:
RBFNN-PSO synchronisation methodSprott B systemZigzag disruption method

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Area of Science:

  • Chaos theory
  • Secure communication
  • Neural networks

Background:

  • Chaotic synchronization research has grown significantly over the last two decades.
  • Various synchronization methods exist, including master-slave, projection, sliding film, and fractional-order synchronization.
  • These methods are applied in chaotic secure communication.

Purpose of the Study:

  • To propose a novel Radial Basis Function Neural Network-Particle Swarm Optimization (RBFNN-PSO) synchronization method.
  • To apply this method to the Sprott B chaotic system, addressing external noise interference.
  • To utilize the synchronized Sprott B system for a robust image encryption scheme.

Main Methods:

  • Developed an RBFNN controller with parameters optimized by the Particle Swarm Optimization (PSO) algorithm.
  • Applied the RBFNN-PSO method to achieve master-slave synchronization for the Sprott B chaotic system in the presence of external noise.
  • Implemented an image encryption system using the synchronized Sprott B chaotic system, incorporating a Zigzag disambiguation method and RGB channel selection.

Main Results:

  • The RBFNN-PSO method effectively overcomes external noise, achieving synchronization in the Sprott B chaotic system.
  • Numerical simulations and analysis confirm the scheme's good performance against external noise.
  • The image encryption system demonstrated successful encryption and decryption, with analysis of encrypted images showing desired random distribution characteristics.

Conclusions:

  • The proposed RBFNN-PSO synchronization method is effective for chaotic systems with external noise.
  • The application to image encryption using the Sprott B chaotic system yields satisfactory security and performance.
  • The study validates the potential of chaotic synchronization in advanced secure communication and data protection.