Work

A Model of Memristive Nanowire Neuron for Recurrent Neural Networks

Year: 2025

Type: conference-paper

Abstract: 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.

Source: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN)

DOI: 10.14428/esann/2025.es2025-104

Authors: Veronica Pistolesi, Andrea Ceni, Gianluca Milano, Carlo Ricciardi, Claudio Gallicchio

Institutions: University of Pisa, Istituto Nazionale di Ricerca Metrologica, Politecnico di Torino

Language: English

Topic: Advanced Memory and Neural Computing

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: bronze

Funders: European Commission, NextGenerationEU

Awards: G3598087732, G972786147