0000000000505314
AUTHOR
Daniel Fernández
Implementation of compact VLSI FitzHugh-Nagumo neurons
In this paper we show a low power and very compact VLSI implementation of a FitzHugh-Nagumo neuron for large network implementations. The circuit consists of only 17 small transistors and two capacitors and consumes less than 23 muW. It is composed of a nonlinear resistor and a lossy active inductor. We demonstrate that a simple low Q active inductor can be used instead of a complex one because the parasitic series resistor can be easily embedded to the FitzHugh-Nagumo model. We also perform a statistical analysis to check the robustness of the circuit against mismatch.
Realistic model of compact VLSI FitzHugh–Nagumo oscillators
In this article, we present a compact analogue VLSI implementation of the FitzHugh–Nagumo neuron model, intended to model large-scale, biologically plausible, oscillator networks. As the model requires a series resistor and a parallel capacitor with the inductor, which is the most complex part of the design, it is possible to greatly simplify the active inductor implementation compared to other implementations of this device as typically found in filters by allowing appreciable, but well modelled, nonidealities. We model and obtain the parameters of the inductor nonideal model as an inductance in series with a parasitic resistor and a second order low-pass filter with a large cut-off freque…