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Found 5 papers, 1 papers with code
A Dual Threshold Analogue Content Addressable Memory
Advances in machine learning and neuromorphic systems are fuelled by the development of architectures required for these applications, such as content addressable memory.
Text Classification in Memristor-based Spiking Neural Networks
We take two approaches to obtain trained spiking neural networks with memristor models: 1) by converting a pre-trained artificial neural network (ANN) to a memristor-based SNN, or 2) by training a memristor-based SNN directly.
A tool for emulating neuromorphic architectures with memristive models and devices
Memristors have shown promising features for enhancing neuromorphic computing concepts and AI hardware accelerators.
An FPGA-based System for Generalised Electron Devices Testing
Electronic systems are becoming more and more ubiquitous as our world digitises.
Frequency Response of Metal-Oxide Memristors
Memristors have been at the forefront of nanoelectronics research for the last decade, offering a valuable component to reconfigurable computing.
Applied Physics
