Effect of the electromagnetic induction on a modified memristive neural map model

Prasina Alexander; Fatemeh Parastesh; Ibrahim Ismael Hamarash; Anitha Karthikeyan; Sajad Jafari; Shaobo He; Prasina Alexander; Fatemeh Parastesh; Ibrahim Ismael Hamarash; Anitha Karthikeyan; Sajad Jafari; Shaobo He

doi:10.3934/mbe.2023793

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 10: 17849-17865. doi: 10.3934/mbe.2023793

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Effect of the electromagnetic induction on a modified memristive neural map model

1.
Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai, India
2.
Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Iran
3.
Electrical Engineering Department, Salahaddin University-Erbil, Kirkuk Rd., Erbil, Kurdistan, Iraq
4.
School of Computer Science and Engineering, University of Kurdistan Hewler, 40m St., Erbil, Kurdistan, Iraq
5.
Department of Electronics and Communication Engineering, Vemu Institute of Technology, Chithoor, India
6.
Department of Electronics and Communications Engineering and University Centre for Research & Development, Chandigarh University, Mohali-140413, Punjab
7.
Health Technology Research Institute, Amirkabir University of Technology (Tehran Polytechnic), Iran
8.
School of Automation and Electronic Information, Xiangtan University, Xiangtan 411105, China

Academic Editor: Yang Kuang

Received: 29 July 2023 Revised: 04 September 2023 Accepted: 11 September 2023 Published: 18 September 2023

The significance of discrete neural models lies in their mathematical simplicity and computational ease. This research focuses on enhancing a neural map model by incorporating a hyperbolic tangent-based memristor. The study extensively explores the impact of magnetic induction strength on the model's dynamics, analyzing bifurcation diagrams and the presence of multistability. Moreover, the investigation extends to the collective behavior of coupled memristive neural maps with electrical, chemical, and magnetic connections. The synchronization of these coupled memristive maps is examined, revealing that chemical coupling exhibits a broader synchronization area. Additionally, diverse chimera states and cluster synchronized states are identified and discussed.
- neural map model,
- memristive map,
- bifurcation,
- synchronization,
- chimera state
Citation: Prasina Alexander, Fatemeh Parastesh, Ibrahim Ismael Hamarash, Anitha Karthikeyan, Sajad Jafari, Shaobo He. Effect of the electromagnetic induction on a modified memristive neural map model[J]. Mathematical Biosciences and Engineering, 2023, 20(10): 17849-17865. doi: 10.3934/mbe.2023793

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Abstract

The significance of discrete neural models lies in their mathematical simplicity and computational ease. This research focuses on enhancing a neural map model by incorporating a hyperbolic tangent-based memristor. The study extensively explores the impact of magnetic induction strength on the model's dynamics, analyzing bifurcation diagrams and the presence of multistability. Moreover, the investigation extends to the collective behavior of coupled memristive neural maps with electrical, chemical, and magnetic connections. The synchronization of these coupled memristive maps is examined, revealing that chemical coupling exhibits a broader synchronization area. Additionally, diverse chimera states and cluster synchronized states are identified and discussed.

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