A Model of Memristive Nanowire Neuron for Recurrent Neural Networks

We propose a novel neural processing unit for artificial neural networks, inspired by the memristive properties of nanowires.Our analysis, framed within the Reservoir Computing paradigm, demonstrates the stability, short-term memory, and fading memory capabilities of the unit.Further experiments on assemblies of nanowire-inspired neurons show promising results in time-series classification tasks.Our introduced approach bridges analog neuromorphic hardware and AI applications, enabling efficient time series processing.