A New Chaotic System with a Self-Excited Attractor: Entropy Measurement, Signal Encryption, and Parameter Estimation.

Guanghui Xu, Yasser Shekofteh, Akif Akgül, Chunbiao Li, Shirin Panahi
Author Information
  1. Guanghui Xu: School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China.
  2. Yasser Shekofteh: Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran 1983969411, Iran. ORCID
  3. Akif Akgül: Department of Electrical and Electronic Engineering, Faculty of Technology, Sakarya University, Serdivan 54187, Turkey.
  4. Chunbiao Li: Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science & Technology, Nanjing 210044, China.
  5. Shirin Panahi: Department of Biomedical Engineering, Amirkabir University of Technology, Tehran 1591634311, Iran.

Abstract

In this paper, we introduce a new chaotic system that is used for an engineering application of the signal encryption. It has some interesting features, and its successful implementation and manufacturing were performed via a real circuit as a random number generator. In addition, we provide a parameter estimation method to extract chaotic model parameters from the real data of the chaotic circuit. The parameter estimation method is based on the attractor distribution modeling in the state space, which is compatible with the chaotic system characteristics. Here, a Gaussian mixture model (GMM) is used as a main part of cost function computations in the parameter estimation method. To optimize the cost function, we also apply two recent efficient optimization methods: WOA (Whale Optimization Algorithm), and MVO (Multi-Verse Optimizer) algorithms. The results show the success of the parameter estimation procedure.

Keywords

References

  1. C R Biol. 2003 Sep;326(9):787-840 [PMID: 14694754]
  2. Nonlinear Dyn. 2017;90(1):749-754 [PMID: 29187777]
  3. Chaos. 1995 Mar;5(1):110-117 [PMID: 12780163]
  4. C R Acad Sci III. 2001 Sep;324(9):773-93 [PMID: 11558325]
  5. Proc Natl Acad Sci U S A. 1991 Mar 15;88(6):2297-301 [PMID: 11607165]
  6. ScientificWorldJournal. 2014;2014:368986 [PMID: 25133225]
  7. Chaos. 2017 Aug;27(8):083101 [PMID: 28863487]
  8. Front Comput Neurosci. 2014 Apr 09;8:40 [PMID: 24782748]
  9. IEEE Eng Med Biol Mag. 2009 Nov-Dec;28(6):18-23 [PMID: 19914883]

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