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Constructing chaotic oscillators with memory components

Author

Listed:
  • Huang, Keyu
  • Li, Chunbiao
  • Cen, Xiaoliang
  • Chen, Guanrong

Abstract

Memory components, including memristors, meminductors and memcapacitors, have special nonlinear dynamical properties and thus applicable for constructing a compact chaotic circuit in parallel or in series. By selecting the restriction of a memory component, chaos control can also be achieved using a single circuit parameter. In this work, three different types of circuit structures are designed to implement memory components for chaos generation. With the help of a voltage-control or a current-control memristor, within a series or a parallel structure, a memristive chaotic oscillator with partial control is built based on the variable boostable systems. The two constructed structures are equivalent and can be mutually tuned, achieving partial amplitude control as well as offset boosting. By constructing a magnetic-control meminductor or a charge-control memcapacitor, the equivalent parallel circuit is built with a meminductor, a capacitor and a resistor, corresponding to the series circuit with a memcapacitor, an inductor and a resistor. It can be applied to realizing the hypogenetic chaotic jerk system even with conditional symmetry. All the designed circuits are physically realized based on PCB, proving the effectiveness of memory components for chaos generation.

Suggested Citation

  • Huang, Keyu & Li, Chunbiao & Cen, Xiaoliang & Chen, Guanrong, 2024. "Constructing chaotic oscillators with memory components," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).
  • Handle: RePEc:eee:chsofr:v:183:y:2024:i:c:s0960077924004697
    DOI: 10.1016/j.chaos.2024.114917
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    References listed on IDEAS

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    1. Li, Kexin & Bao, Bocheng & Ma, Jun & Chen, Mo & Bao, Han, 2022. "Synchronization transitions in a discrete memristor-coupled bi-neuron model," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    2. Lai, Qiang & Lai, Cong & Zhang, Hui & Li, Chunbiao, 2022. "Hidden coexisting hyperchaos of new memristive neuron model and its application in image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    3. Li, Yongxin & Li, Chunbiao & Zhong, Qing & Zhao, Yibo & Yang, Yong, 2024. "Coexisting hollow chaotic attractors within a steep parameter interval," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
    4. Lin, Hairong & Wang, Chunhua & Du, Sichun & Yao, Wei & Sun, Yichuang, 2023. "A family of memristive multibutterfly chaotic systems with multidirectional initial-based offset boosting," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    5. Deng, Quanli & Wang, Chunhua & Lin, Hairong, 2024. "Memristive Hopfield neural network dynamics with heterogeneous activation functions and its application," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    Full references (including those not matched with items on IDEAS)

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