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Spike Neural Network (SNN)
Artificial neural network that communicates via discrete impulses (spikes) rather than continuous values, thus mimicking the biological functioning of the brain.
Neuromorphic Processor
Processing unit specifically designed to simulate the architecture and functioning of biological neural circuits using digital components.
Digital Synaptic Plasticity
Digital implementation of the ability of synapses to strengthen or weaken their connections over time, essential for neuromorphic learning.
Asynchronous Neuromorphic Computing
Computing approach where neurons operate independently without a global synchronized clock, reproducing the parallel processing of the brain.
Digital Neuromorphic Core
Basic computing unit in a digital neuromorphic architecture, containing digitally simulated neurons and synapses.
STDP Digital Implementation
Digital version of Spike-Timing-Dependent Plasticity, where synaptic modification depends on the relative time between presynaptic and postsynaptic spikes.
Integrate-and-Fire Digital Neuron
Digital neuron model that accumulates inputs until a threshold, then generates a spike and resets, implemented in binary logic.
Neuromorphic Memory Architecture
Memory structure specially designed to efficiently store and access synaptic weights and neural states in digital neuromorphic systems.
Digital Neurotransmitter Simulation
Modélisation numérique des mécanismes de transmission chimique entre neurones pour reproduire les comportements synaptiques complexes.
Binary Weight Neural Network
Type de réseau neuronal où les poids synaptiques sont quantifiés en valeurs binaires (-1 ou +1), optimisé pour le calcul neuromorphique numérique.
Neuromorphic Routing Network
Système d'interconnexion numérique spécialisé pour acheminer les spikes entre neurones dans une architecture neuromorphique distribuée.
Digital Axonal Delay Line
Implémentation numérique des délais de propagation axonaux qui affectent le timing des spikes dans les réseaux neuronaux biologiques.
Neuromorphic Power Gating
Technique de gestion d'énergie qui désactive sélectivement les composants neuronaux inactifs pour optimiser la consommation dans les circuits neuromorphiques numériques.