Fractional-Order Memristive Wilson Neuron Model: Dynamical Analysis and Synchronization Patterns
Gayathri Vivekanandan, Mahtab Mehrabbeik, Hayder Natiq, Karthikeyan Rajagopal, Esteban Tlelo‐Cuautle
Abstract
Fractional nonlinear systems have been considered in many fields due to their ability to bring memory-dependent properties into various systems. Therefore, using fractional derivatives to model real-world phenomena, such as neuronal dynamics, is of significant importance. This paper presents the fractional memristive Wilson neuron model and studies its dynamics as a single neuron. Furthermore, the collective behavior of neurons is researched when they are locally and diffusively coupled in a ring topology. It is found that the fractional-order neurons are bistable in some values of the fractional order. Additionally, complete synchronization, lag synchronization, phase synchronization, and sine-like synchronization patterns can be observed in the constructed network with different fractional orders.