Multistable State and Phase Synchronization of Memristor-coupled Heterogeneous Memristive Cellular Neural Network

WU Huagan; BIAN Yixuan; CHEN Mo; XU Quan

doi:10.11999/JEIT240010

Volume 46 Issue 9

Sep. 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(9): 3818-3826

WU Huagan, BIAN Yixuan, CHEN Mo, XU Quan. Multistable State and Phase Synchronization of Memristor-coupled Heterogeneous Memristive Cellular Neural Network[J]. Journal of Electronics & Information Technology, 2024, 46(9): 3818-3826. doi: 10.11999/JEIT240010

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WU Huagan, BIAN Yixuan, CHEN Mo, XU Quan. Multistable State and Phase Synchronization of Memristor-coupled Heterogeneous Memristive Cellular Neural Network[J]. Journal of Electronics & Information Technology, 2024, 46(9): 3818-3826. doi: 10.11999/JEIT240010

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Multistable State and Phase Synchronization of Memristor-coupled Heterogeneous Memristive Cellular Neural Network

doi: 10.11999/JEIT240010

School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China

Funds: The National Natural Science Foundation of China (62371073, 12172066, 52277001), The Postgraduate Education Reform Projects of Jiangsu Province (KYCX23_3181)

Received Date: 2024-01-16
Rev Recd Date: 2024-04-02

Available Online: 2024-04-23

Publish Date: 2024-09-26

Abstract

Abstract

Memristors have a natural plasticity that enables silicon-based neurons and nano-synapses with similar or the same mechanisms as biological neurons and synapses. Using a memristor as a synapse to couple two heterogeneous memristive cellular neural networks, a memristor-coupled heterogeneous cellular neural network is constructed in this paper. The coupled network contains a space equilibrium set related to the initial value conditions of memristor synapse and subnets, which can exhibit complex dynamic evolution. The multi-stable behaviors of the coupling network, such as stable point, period, chaos, hyperchaos and unbounded oscillation, which depend on the initial value conditions, are revealed by numerical simulation method. In addition, under the control of memristor synapse, two heterogeneous subnets can achieve phase synchronization. Finally, the experimental verification of the circuit is completed based on STM32 MCU hardware platform.
- Memristor,
- Cellular neural network,
- Heterogeneous network,
- Multi-stable state,
- Phase synchronization

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References(23)

References

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