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Mostrando ítems 1-10 de 23
Artículo
Liquid State Machine on SpiNNaker for Spatio-Temporal Classification Tasks
(Frontiers Media S.A., 2022-03-14)
Liquid State Machines (LSMs) are computing reservoirs composed of recurrently connected Spiking Neural Networks which have attracted research interest for their modeling capacity of biological structures and as promising ...
Artículo
Asynchronous Spiking Neurons, the Natural Key to Exploit Temporal Sparsity
(IEEE Computer Society, 2019)
Inference of Deep Neural Networks for stream signal (Video/Audio) processing in edge devices is still challenging. Unlike the most state of the art inference engines which are efficient for static signals, our brain is ...
Artículo
CMOS Front End for Interfacing Spin-Hall Nano-Oscillators for Neuromorphic Computing in the GHz Range
(MDPI, 2023-01)
Spin-Hall-effect nano-oscillators are promising beyond the CMOS devices currently avail- able, and can potentially be used to emulate the functioning of neurons in computational neuromor- phic systems. As they oscillate ...
Artículo
On Real-Time AER 2-D Convolutions Hardware for Neuromorphic Spike-Based Cortical Processing
(IEEE Computer Society, 2008)
In this paper, a chip that performs real-time image convolutions with programmable kernels of arbitrary shape is presented. The chip is a first experimental prototype of reduced size to validate the implemented circuits ...
Artículo
An event-based classifier for Dynamic Vision Sensor and synthetic data
(Frontiers Media, 2017)
This paper introduces a novel methodology for training an event-driven classifier within a Spiking Neural Network (SNN) System capable of yielding good classification results when using both synthetic input data and real ...
Artículo
Retinomorphic Event-Based Vision Sensors: Bioinspired Cameras With Spiking Output
(IEEE Computer Society, 2014)
State-of-the-art image sensors suffer from significant limitations imposed by their very principle of operation. These sensors acquire the visual information as a series of “snapshot” images, recorded at discrete points ...
Artículo
Effect of Device Mismatches in Differential Oscillatory Neural Networks
(IEEE, 2023-02)
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 implementation is component mismatches which cause ...
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
A memristive nanoparticle/organic hybrid synapstor for neuro-inspired computing.
(Wiley, 2011)
A large effort is devoted to the research of new computing paradigms associated with innovative nanotechnologies that should complement and/or propose alternative solutions to the classical Von Neumann/CMOS (complementary ...
Artículo
Active Perception with Dynamic Vision Sensors. Minimum Saccades with Optimum Recognition
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Vision processing with Dynamic Vision Sensors (DVS) is becoming increasingly popular. This type of bio-inspired vision sensor does not record static scenes. DVS pixel activity relies on changes in light intensity. In ...