Bifurcation investigation, phase synchronization and FPGA implementation of a new photosensitive Fitz Hugh Nagumo neuron based meminductor

This paper focuses on the estimation of the nonlinear encoding and responses of a photosensitive Fitz Hugh Nagumo (FHN) neuron-based-meminductor and provides a relevant analysis of its phase synchronization. In the pattern, a Fitz Hugh–Nagumo neuron connected to a meminductor is activated by a photocell, and a time-varying current source is generated by the presence of external optical signals. This coupling is a benchmark circuit with memory similar to artificial eyes with the ability to capture and encode external signals. It is designed with the aim of studying the dynamics of a neuron with a memory effect highlighted through the meminductor. An appropriate dynamical analysis is provided using standard indicators such as bifurcations to point out thorough transitions and the nature of the electrical neuronal activities. Some couplings between two FHN neurons with meminductor using hybrid synapses composed of passive electronic components are achieved. Relevant tools are used to analyze the stability of the synchronization which gives prominent details on the selection of the appropriate coupling. The energy balance of the external system is evaluated which gives the effort to achieve encoding signals and also proves the feasibility of the proposal in real-time implementation. Simulations are performed on FPGA. The results present a good agreement. In many engineering applications, the detection of optical signals is inescapable as well as the synchronization of its signals for the transmission of the stimuli. These results could be useful for the designer.