Fractional order memcapacitive neuromorphic elements reproduce and predict neuronal function.

There is an increasing need to implement neuromorphic systems that are both energetically and computationally efficient. There is also great interest in using electric elements with memory, memelements, that can implement complex neuronal functions intrinsically. A feature not widely incorporated in neuromorphic systems is history-dependent action potential time adaptation which is widely seen in real cells.

Low-Voltage Low-Power Integrable CMOS Circuit Implementation of Integer- and Fractional-Order FitzHugh-Nagumo Neuron Model.

The low-voltage low-power sinh-domain (SD) implementations of integer- and fractional-order FitzHugh-Nagumo (FHN) neuron model have been introduced in this paper. Besides, the effect of fractional-orders on the external excitation current and dynamics of the neuron has been examined in this paper. The proposed SD designs of FHN neuron model have the benefits of: 1) low-voltage operation; 2) integrability, due to resistor-less design and the employment of only grounded components; 3) electronic tunability of performance parameters; and 4) low-power implementation due to the inherent properties of SD technique.