Work

Utilizing rate-independent hysteresis for analog computing

Year: 2025

Type: article

Abstract: Physical systems exhibiting hysteresis are increasingly being used in neuromorphic and in-memory computing research. Generally, the resistance switching of devices with rate-independent hysteresis are being investigated for their use as trainable weights in neural networks, whereas the dynamics of devices showing rate-dependent hysteresis are being investigate for their potential as nodes, for example in reservoir computing systems. In our work we instead investigate the computing potential of a simple rate-independent hysteresis system. We show that by driving a system of only two linear branches with time-multiplexed inputs it is possible to generate nonlinear transforms and perform timeseries prediction tasks.

Source: Neuromorphic Computing and Engineering

DOI: 10.1088/2634-4386/ae1bcf

Authors: Lina Jaurigue, Kathy Lüdge

Institution: Technische Universität Ilmenau

Language: English

Topic: Advanced Memory and Neural Computing

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,835

Funder: Carl-Zeiss-Stiftung