Brain-Inspired Self-Organization with Cellular Neuromorphic Computing for Multimodal Unsupervised Learning
Cortical plasticity is one of the main features that enable our ability to learn and adapt in our environment. Indeed, the cerebral cortex self-organizes itself through structural and synaptic plasticity mechanisms that are very likely at the basis of an extremely interesting characteristic of the h...
Main Authors: | Lyes Khacef, Laurent Rodriguez, Benoît Miramond |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-10-01
|
Series: | Electronics |
Subjects: | |
Online Access: | https://www.mdpi.com/2079-9292/9/10/1605 |
Similar Items
-
Editorial: Multimodal behavior from animals to bio-inspired robots
by: Yaguang Zhu, et al.
Published: (2023-02-01) -
Dual functional states of working memory realized by memristor-based neural network
by: Hongzhe Wang, et al.
Published: (2023-06-01) -
Spike-based local synaptic plasticity: a survey of computational models and neuromorphic circuits
by: Lyes Khacef, et al.
Published: (2023-01-01) -
Stability of Stochastic Networks with Proportional Delays and the Unsupervised Hebbian-Type Learning Algorithm
by: Famei Zheng, et al.
Published: (2023-11-01) -
Trajectory design via unsupervised probabilistic learning on optimal manifolds
by: Cosmin Safta, et al.
Published: (2022-01-01)