Fractal Performance Under Magnetization Procedures of Fractional Memristive Wilson Neuron Dynamical Model

Abstract

The non-integer neuron dynamical models are feasible for accurate prediction and perfect estimation of magnetization and de-magnetization in complicated physiological environments within reliable fractal-fractional neuronal modeling. The memristive Wilson neuron model is proposed under the comparative performance of two types of fractal-fractional differentials with two different types of kernels based on two different memories. The non-classical memristive Wilson neuron model with and without magnetization is simulated for numerical schemes by means of linear multi-step integration method. The numerical simulations are traced out by discretizing continuum processes of spatial and time domains for the sake of perfect approximations under singular and non-singular kernel versus local and non-local kernel. By applying the powerful methodology of fractal-fractional differential and integral operators on the memristive Wilson neuron model, the antimonotonicity phenomenon and asymmetric coexisting electrical activities have been explored intensively to widen the neuron-based engineering applications. Remarkably, our results based on magnetization and de-magnetization procedures of Wilson neuron model have imitated the neuron activities under electrophysiological environment.