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A Novel Butterfly-Attractor Dynamical System Without Equilibrium: Theory, Synchronization, and Application in Secure Communication

  • Viet Thanh Pham
  • , Victor Kamdoum Tamba
  • , Fernando E. Serrano
  • , Giuseppe Grassi
  • , Shaher Momani
  • Industrial University of Ho Chi Minh City
  • Université de Dschang
  • National Autonomous University of Honduras
  • Polytechnic University of Catalonia
  • University of Salento
  • University of Jordan

Research output: Contribution to journalArticlepeer-review

Abstract

The theory underlying non-linear dynamical systems remains essential for understanding complex behaviors in science and engineering. In this study, we propose a new chaotic dynamical system that exhibits a butterfly-shaped attractor without any equilibrium point. Despite its compact structure comprising only five terms, the system demonstrates rich chaotic behavior distinct from conventional oscillator models. Detailed modeling and dynamical analyses are conducted to confirm the presence of chaos and to characterize the system’s sensitivity to initial conditions. Furthermore, synchronization of the proposed dynamical system is investigated using both identical and non-identical control algorithms. In the identical case, the activation function of the neural network is governed by the butterfly oscillator dynamics, whereas in the non-identical case, a sigmoidal activation function is employed. The proposed synchronization algorithms enable faster convergence by pinning a subset of nodes in the network. Finally, a practical implementation of the conceived dynamical system in an encryption framework is presented, with the aim to demonstrate its feasibility and potential application in secure communication systems. The results highlight the effectiveness of the proposed approach for both theoretical exploration and engineering applications involving chaotic dynamical systems.

Original languageEnglish
Article number18
JournalAlgorithms
Volume19
Issue number1
DOIs
StatePublished - Jan 2026

Keywords

  • chaos
  • controller
  • neural network
  • neuron
  • synchronization

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