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Ponencia
ConvNets Experiments on SpiNNaker
(IEEE Computer Society, 2015)
The SpiNNaker Hardware platform allows emulating generic neural network topologies, where each neuronto- neuron connection is defined by an independent synaptic weight. Consequently, weight storage requires an ...
Ponencia
Event-Driven Configurable Module with Refractory Mechanism for ConvNets on FPGA
(IEEE Computer Society, 2018)
We have developed a fully configurable event-driven convolutional module with refractory period mechanism that can be used to implement arbitrary Convolutional Neural Networks (ConvNets) on FPGAs following a 2D array ...
Ponencia
Event-driven stereo vision with orientation filters
(IEEE Computer Society, 2014)
The recently developed Dynamic Vision Sensors (DVS) sense dynamic visual information asynchronously and code it into trains of events with sub-micro second temporal resolution. This high temporal precision makes the ...
Ponencia
On neuromorphic spiking architectures for asynchronous STDP memristive systems
(IEEE Computer Society, 2010)
Neuromorphic circuits and systems techniques have great potential for exploiting novel nanotechnology devices, which suffer from great parametric spread and high defect rate. In this paper we explore some potential ways ...
Ponencia
High-Speed Serial Interfaces for Event-Driven Neuromorphic Systems
(IEEE Computer Society, 2015)
Neuromorphic Engineering is the discipline of building sensory processing artificial systems inspired in the neural processing found in living beings. Biological neural brains show massive connectivity among neurons, ...
Ponencia
A signed spatial contrast event spike retina chip
(IEEE Computer Society, 2010)
Reported AER (Address Event Representation) contrast retinae perform a contrast computation based on the ratio between a pixel's local light intensity and a spatially weighted average of its neighbourhood. This results in ...
Ponencia
Design of adaptive nano/CMOS neural architectures
(IEEE Computer Society, 2012)
Memristive devices are a promising technology to implement dense learning synapse arrays emulating the high memory capacity and connectivity of biological brains. Recently, the implementation of STDP learning in memristive ...