Silicon neuron dedicated to memristive spiking neural networks
Résumé
Since memristor came out in 2008, neuromorphic designers investigated the possibility of using memristors as plastic synapses due to their intrinsic properties of plasticity and weight storage. In this paper we will present a silicon neuron compatible with memristive synapses in order to build analog neural network. This neuron mainly includes current conveyor (CCII) for driving memristor as excitatory or inhibitory synapses and spike generator whose waveform is dedicated to synaptic plasticity algorithm based on Spike Timing Dependent Plasticity (STDP). This silicon neuron has been fabricated, characterized and finally connected with a ferroelectric memristor to validate the synaptic weight updating principle.
Mots clés
CCII
STDP
analog neural network
current conveyor
excitatory synapses
ferroelectric memristor
inhibitory synapses
memristive spiking neural networks
plastic synapses
silicon neuron
spike generator
spike timing dependent plasticity
synaptic plasticity algorithm
synaptic weight updating principle
weight storage