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Mostrando ítems 1-10 de 15
Artículo
How Frequency Injection Locking Can Train Oscillatory Neural Networks to Compute in Phase
(IEEE, 2022)
Brain-inspired computing employs devices and architectures that emulate biological functions for more adaptive and energy-efficient systems. Oscillatory neural networks (ONNs) are an alternative approach in emulating ...
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
Hardware Implementation of Differential Oscillatory Neural Networks Using VO 2-Based Oscillators and Memristor-Bridge Circuits
(Frontiers Media, 2021)
Oscillatory Neural Networks (ONNs) are currently arousing interest in the research community for their potential to implement very fast, ultra-low-power computing tasks by exploiting specific emerging technologies. From ...
Ponencia
Neuron fault tolerance in spiking neural networks
(Institute of Electrical and Electronics Engineers. IEEE, 2021)
The error-resiliency of Artificial Intelligence (AI) hardware accelerators is a major concern, especially when they are deployed in mission-critical and safety-critical applications. In this paper, we propose a neuron ...
Artículo
Digital Implementation of Oscillatory Neural Network for Image Recognition Applications
(Frontiers Media, 2021)
Computing paradigm based on von Neuman architectures cannot keep up with the ever-increasing data growth (also called “data deluge gap”). This has resulted in investigating novel computing paradigms and design approaches ...
Artículo
Oscillatory Neural Networks Using VO2 Based Phase Encoded Logic
(Frontiers Media, 2021)
Nano-oscillators based on phase-transition materials are being explored for the implementation of different non-conventional computing paradigms. In particular, vanadium dioxide (VO2) devices are used to design autonomous ...
Tesis Doctoral
Memristor Based Event Driven Neuromorphic Nano-CMOS Processor
(2021-02-19)
‘Neuromorphic engineering’ has been showing significant developments in recent days. The word ‘neuromorphic’ was first coined by Caver Mead, which is morphing biological brain on-chip [1]. The main idea is to use the ...
Ponencia
Event data downscaling for embedded computer vision
(SciTePress, 2022-02)
Event cameras (or silicon retinas) represent a new kind of sensor that measure pixel-wise changes in brightness and output asynchronous events accordingly. This novel technology allows for a sparse and energy-efficient ...
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, ...