Cargando…
Synchronization in STDP-driven memristive neural networks with time-varying topology
Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed to achieve robust and enduring synchronization in neurons driven by spike-timing-dependent plasticity (STDP) and tempor...
Autores principales: | Yamakou, Marius E., Desroches, Mathieu, Rodrigues, Serafim |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10651826/ https://www.ncbi.nlm.nih.gov/pubmed/37656327 http://dx.doi.org/10.1007/s10867-023-09642-2 |
Ejemplares similares
-
A compound memristive synapse model for statistical learning through STDP in spiking neural networks
por: Bill, Johannes, et al.
Publicado: (2014) -
A memristive plasticity model of voltage-based STDP suitable for recurrent bidirectional neural networks in the hippocampus
por: Diederich, Nick, et al.
Publicado: (2018) -
Asymptotic Synchronization of Memristive Cohen-Grossberg Neural Networks with Time-Varying Delays via Event-Triggered Control Scheme
por: Yao, Wei, et al.
Publicado: (2022) -
Finite-time complete periodic synchronization of memristive neural networks with mixed delays
por: Brahmi, Hajer, et al.
Publicado: (2023) -
Projective Synchronization of Delayed Uncertain Coupled Memristive Neural Networks and Their Application
por: Han, Zhen, et al.
Publicado: (2023)