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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 ...
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 ...
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
A CMOL-Like Memristor-CMOS Neuromorphic Chip-Core Demonstrating Stochastic Binary STDP
(Institute of Electrical and Electronics Engineers Inc., 2022-12)
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 memristors would be fabricated at the ...
Artículo
A CMOS-memristor hybrid system for implementing stochastic binary spike timing-dependent plasticity
(Royal Society Publishing, 2022)
This paper describes a fully experimental hybrid system in which a 4 × 4 memristive crossbar spiking neural network (SNN) was assembled using custom high-resistance state memristors with analogue CMOS neurons fabricated ...