2 citations · 2 across the 3 of their papers we have counts for
3 papers
Modeling Memristor-Based Neural Networks with Manhattan Update: Trade-offs in Learning Performance and Energy Consumption
Walter Quiñonez, María José Sánchez, Diego Rubi
We present a systematic study of memristor based neural networks trained with the hardware-friendly Manhattan update rule, focusing on the trade offs between learning performance a…
Synaptic plasticity in Co/Nb:STO memristive devices: The role of oxygen vacancies
Walter Quiñonez, Anouk Goossens, Diego Rubi +2
Neuromorphic computing aims to develop energy-efficient devices that mimic biological synapses. One promising approach involves memristive devices that can dynamically adjust their…
Effect of memristorś potentiation-depression curves peculiarities in the convergence of physical perceptrons
Walter Quiñonez, María José Sánchez, Diego Rubi
Neuromorphic computing aims to emulate the architecture and information processing mechanisms of the mammalian brain. This includes the implementation by hardware of neural network…