activity
20202022
most citedFully-parallel Convolutional Neural Network Hardware

1 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY20221 cited

Effect of Device Mismatches in Differential Oscillatory Neural Networks

Jafar Shamsi, María José Avedillo, Bernabé Linares-Barranco +1

Analog implementation of Oscillatory Neural Networks (ONNs) has the potential to implement fast and ultra-low-power computing capabilities. One of the drawbacks of analog implement…

cs.ET20221 cited

A CMOL-Like Memristor-CMOS Neuromorphic Chip-Core Demonstrating Stochastic Binary STDP

L. A. Camuñas-Mesa, E. Vianello, C. Reita +2

The advent of nanoscale memristors raised hopes of being able to build CMOL (CMOS/nanowire/moLecular) type ultra-dense in-memory-computing circuit architectures. In CMOL, nanoscale…

cs.CV20211 cited

Foveal-pit inspired filtering of DVS spike response

Shriya T. P. Gupta, Pablo Linares-Serrano, Basabdatta Sen Bhattacharya +1

In this paper, we present results of processing Dynamic Vision Sensor (DVS) recordings of visual patterns with a retinal model based on foveal-pit inspired Difference of Gaussian (…

cs.ET20211 cited

Experimental Body-input Three-stage DC offset Calibration Scheme for Memristive Crossbar

Charanraj Mohan, L. A. Camuñas-Mesa, Elisa Vianello +4

Reading several ReRAMs simultaneously in a neuromorphic circuit increases power consumption and limits scalability. Applying small inference read pulses is a vain attempt when offs…

cs.NE20201 cited

Fully-parallel Convolutional Neural Network Hardware

Christiam F. Frasser, Pablo Linares-Serrano, V. Canals +3

A new trans-disciplinary knowledge area, Edge Artificial Intelligence or Edge Intelligence, is beginning to receive a tremendous amount of interest from the machine learning commun…