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Aleksandra KOROLEVA

Study and development of La2NiO4 memristive devices for bio-inspired computing


Keywords: Memristive device, neuromorphic computing, valence change memory

Abstract: This project focuses on the use of La2NiO4 devices as artificial synapses for bio-inspired computing architectures, i.e., Spiking Neural Networks (SNNs) with a bio-inspired learning rule. The learning is applied on each synapse independently of the global state of the network; therefore, the synapse must be doted of computation capabilities. The goal of the project is to demonstrate, at small scale, the feasibility of a La2NiO4-based SNN and understand the main advantages and shortcomings (from technology and application) such that concomitant optimization of device and algorithm can be performed to guarantee the achievement of a truly efficient bio-inspired electronic system.


Thesis director: Ioana VATAJELU (TIMA - AMfoRS)
Thesis supervisor: Monica BURRIEL LOPEZ (LMGP)
Thesis started on: Nov. 2022
Doctoral school: EEATS

Submitted on November 29, 2022

Updated on December 12, 2023