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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
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 ...