Year: 2021
Type: dissertation
Abstract: We present simulation results based on a model of self–assembled nanowire networks with memristive junctions and neural network–like topology. We analyse the dynamical voltage distribution in response to an applied bias and explain the network conductance fluctuations observed in previous experimental studies. We show I − V curves under AC stimulation and compare these to other bulk memristors. We then study the capacity of these nanowire networks for neuro-inspired reservoir computing by demonstrating higher harmonic generation and short/long–term memory. Benchmark tasks in a reservoir computing framework are implemented. The tasks include nonlinear wave transformation, wave auto-generation, and hand-written digit classification.
Author: Kaiwei Fu
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3198093968