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Mostrando ítems 1-5 de 5
Ponencia
Experimental Body-input Three-stage DC offset Calibration Scheme for Memristive Crossbar
(IEEE, 2020)
Reading several ReRAMs simultaneously in a neuromorphic circuit increases power consumption and limits scalability. Applying small inference read pulses is a vain attempt when offset voltages of the read-out circuit are ...
Ponencia
Implementation of binary stochastic STDP learning using chalcogenide-based memristive devices
(IEEE, 2021-04)
The emergence of nano-scale memristive devices encouraged many different research areas to exploit their use in multiple applications. One of the proposed applications was to implement synaptic connections in bio-inspired ...
Artículo
Event-driven implementation of deep spiking convolutional neural networks for supervised classification using the SpiNNaker neuromorphic platform
(Elsevier, 2020)
Neural networks have enabled great advances in recent times due mainly to improved parallel computing capabilities in accordance to Moore’s Law, which allowed reducing the time needed for the parameter learning of complex, ...
Artículo
Neuromorphic Low-Power Inference on Memristive Crossbars With On-Chip Offset Calibration
(IEEE, 2021-03)
Monolithic integration of silicon with nano-sized Redox-based resistive Random-Access Memory (ReRAM) devices opened the door to the creation of dense synaptic connections for bio-inspired neuromorphic circuits. One ...
Ponencia
Foveal-pit inspired filtering of DVS spike response
(Institute of Electrical and Electronics Engineers Inc. (IEEE), 2021)
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 (DoG) filters. A DVS sensor was stimulated ...