A Rectified Linear Unit-Based Memristor-Enhanced Morris-Lecar Neuron Model

被引:1
|
作者
Almatroud, Othman Abdullah [1 ]
Pham, Viet-Thanh [2 ]
Rajagopal, Karthikeyan [3 ,4 ]
机构
[1] Univ Hail, Fac Sci, Dept Math, Hail 2440, Saudi Arabia
[2] Ind Univ Ho Chi Minh City, Fac Elect Technol, Ho Chi Minh City 70000, Vietnam
[3] Easwari Engn Coll, Ctr Res, Chennai 600089, India
[4] SRM Inst Sci & Technol Ramapuram, Ctr Res, Chennai, India
关键词
Morris-Lecar neuron model; ReLU-based memristor; bifurcation; Lyapunov exponent; multistability; synchronization; chimera state; CHIMERA STATES; SYNCHRONIZATION; BIFURCATION; PATTERNS; NETWORK;
D O I
10.3390/math12192970
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper introduces a modified Morris-Lecar neuron model that incorporates a memristor with a ReLU-based activation function. The impact of the memristor on the dynamics of the ML neuron model is analyzed using bifurcation diagrams and Lyapunov exponents. The findings reveal chaotic behavior within specific parameter ranges, while increased magnetic strength tends to maintain periodic dynamics. The emergence of various firing patterns, including periodic and chaotic spiking as well as square-wave and triangle-wave bursting is also evident. The modified model also demonstrates multistability across certain parameter ranges. Additionally, the dynamics of a network of these modified models are explored. This study shows that synchronization depends on the strength of the magnetic flux, with synchronization occurring at lower coupling strengths as the magnetic flux increases. The network patterns also reveal the formation of different chimera states, such as traveling and non-stationary chimera states.
引用
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页数:10
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