Research within the NEO group focuses into bio-inspired electronics using functional oxides, for the next generation of AI hardware. The multi-level, non-volatile memories are the building blocks for Compute in Memory architectures. The unique properties of ferroelectric switching are leveraged to mimic plasticity in biological synapses.
The nanofabrication of the neuromorphic devices is performed using the state-of-the-art facilities at the Binnig and Rohrer Nanotechnology Center (BRNC).
Repository with code to generate microfabrication masks for the ViTFOX project. This repository represents the month 6 deliverable.
Python 1
Forked from arc-instruments/pyarc2
Not so low level Python bindings for libarc2
Rust
Forked from PaU1570/msc_project
Energy-convergence trade off for the training of neural networks on bio-inspired hardware
Jupyter Notebook 1
Concurrent electrical characterisation platform for the integration of ferroelectric oxides with complex oxides.
Python
Part of Linyue Weng's project
Part of Linyue Weng's project
Personalized Spiking Neural Networks with Ferroelectric Synapses for EEG Signal Processing
This repository contains programs developed to analyze data generated with the FE tester in the lab. The goal is to provide tools for processing and analyzing the following file types: Fatigue (DHM and CV) DHM CV PUND The programs automatically generate plots and convert raw data files into CSV format for easier handling and visualization.
Concurrent electrical characterisation platform for the integration of ferroelectric oxides with complex oxides.
Energy-convergence trade off for the training of neural networks on bio-inspired hardware
Repository with code to generate microfabrication masks for the ViTFOX project. This repository represents the month 6 deliverable.
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