Systèmes neuromorphiques : Etude et implantation de fonctions d'apprentissage et de plasticité
type: Dataset
contact point: Organization
  fn: CCSD
keyword: hodgkin-et-huxley
keyword: systemes-neuromorphiques
keyword: spitronengineering-sciences-physicselectronics
keyword: stdp
keyword: pynn
keyword: theses
keyword: infoeu-reposemanticsdoctoralthesis
keyword: reseaux-de-neurones
keyword: neurosciences-computationnelles
keyword: plasticite
landing page: https://theses.hal.science/tel-00982090
description: In this work, we have investigated the e ffect of input noise patterns on synaptic plasticity applied to a neural network. The study was realised using a neuromorphic hardware simulation system. We have implemented a neural conductance model based on Hodgkin and Huxley formalism, and a biophysical model for plasticity. The tasks performed during this thesis project included the con figuration of the system, the development of software tools, the analysis tools to explore experimental results, and the development of the software modules for the remote access to the system via Internet using PyNN scripts (PyNN is a neural network description language commonly used in computational neurosciences).
issued: 2026-05-05T13:38:11.796617
language: fr
modified: 2026-05-05T13:38:11.796622

Systèmes neuromorphiques : Etude et implantation de fonctions d'apprentissage et de plasticité
type: Distribution
access URL: https://theses.hal.science/tel-00982090
format: HTML
issued: 2026-05-05T13:38:11.803524
modified: 2026-05-05T13:38:11.785228

test_moissonnage_selune
type: Agent