Fractional Integrate-and-Fire Neuron: Analog Realization and Application to Neuromorphic Control

Silicon neurons are bioinspired circuits with the capability to reproduce the pulse frequency modulation observed in actual neurons. Among them, fractional neurons are known to emulate the adaptation of real neurons, which refers to the change in the pulse frequency despite a constant amplitude at the input. In the context of neuromorphic control, silicon neurons are introduced in a closed loop structure to encode the control signal into pulses. This paper proposes an analog realization of a fractional integrate-and-fire (I& F) neuron with reset, which is validated through physical modeling in the MATLAB/Simulink environment. Furthermore, initial tests utilizing fractional neurons in neuromorphic control are carried out.