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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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A New Chaotic System with a Self-Excited Attractor: Entropy Measurement, Signal Encryption, and Parameter Estimation.

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Summary

We developed a new chaotic system for secure signal encryption and a real circuit random number generator. A novel parameter estimation method using Gaussian mixture models and optimization algorithms successfully extracted chaotic model parameters from circuit data.

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Area of Science:

  • Engineering
  • Chaos Theory
  • Signal Processing

Background:

  • Chaotic systems offer unique properties for secure applications.
  • Real-world implementation of chaotic systems is crucial for practical use.
  • Accurate parameter estimation is essential for modeling and controlling chaotic circuits.

Purpose of the Study:

  • Introduce a novel chaotic system for signal encryption.
  • Develop and validate a parameter estimation method for chaotic circuits.
  • Implement the chaotic system as a hardware random number generator.

Main Methods:

  • Designed and manufactured a physical chaotic circuit.
  • Developed a parameter estimation technique based on attractor distribution modeling.
  • Utilized Gaussian Mixture Models (GMM) for cost function computation.
  • Employed Whale Optimization Algorithm (WOA) and Multi-Verse Optimizer (MVO) for parameter optimization.

Main Results:

  • Successfully implemented a chaotic system in a real circuit.
  • Demonstrated the effectiveness of the parameter estimation method.
  • Validated the chaotic system as a random number generator.
  • Achieved accurate extraction of chaotic model parameters.

Conclusions:

  • The proposed chaotic system is suitable for signal encryption applications.
  • The developed parameter estimation method accurately models chaotic circuits.
  • The integration of GMM, WOA, and MVO enhances parameter estimation accuracy.