Cargando…
A Swarm Optimization Solver Based on Ferroelectric Spiking Neural Networks
As computational models inspired by the biological neural system, spiking neural networks (SNN) continue to demonstrate great potential in the landscape of artificial intelligence, particularly in tasks such as recognition, inference, and learning. While SNN focuses on achieving high-level intellige...
Autores principales: | Fang, Yan, Wang, Zheng, Gomez, Jorge, Datta, Suman, Khan, Asif I., Raychowdhury, Arijit |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6700359/ https://www.ncbi.nlm.nih.gov/pubmed/31456659 http://dx.doi.org/10.3389/fnins.2019.00855 |
Ejemplares similares
-
Stochastic IMT (Insulator-Metal-Transition) Neurons: An Interplay of Thermal and Threshold Noise at Bifurcation
por: Parihar, Abhinav, et al.
Publicado: (2018) -
Supervised Learning in All FeFET-Based Spiking Neural Network: Opportunities and Challenges
por: Dutta, Sourav, et al.
Publicado: (2020) -
Design of neuro-swarming computational solver for the fractional Bagley–Torvik mathematical model
por: Guirao, Juan L. G., et al.
Publicado: (2022) -
Bearing fault diagnosis based on particle swarm optimization fusion convolutional neural network
por: Liu, Xian, et al.
Publicado: (2022) -
Vertex coloring of graphs via phase dynamics of coupled oscillatory networks
por: Parihar, Abhinav, et al.
Publicado: (2017)