Cargando…
Stabilizing patterns in time: Neural network approach
Recurrent and feedback networks are capable of holding dynamic memories. Nonetheless, training a network for that task is challenging. In order to do so, one should face non-linear propagation of errors in the system. Small deviations from the desired dynamics due to error or inherent noise might ha...
Autores principales: | Ben-Shushan, Nadav, Tsodyks, Misha |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5741269/ https://www.ncbi.nlm.nih.gov/pubmed/29232710 http://dx.doi.org/10.1371/journal.pcbi.1005861 |
Ejemplares similares
-
Persistent Activity in Neural Networks with Dynamic Synapses
por: Barak, Omri, et al.
Publicado: (2007) -
Correction: Persistent Activity in Neural Networks with Dynamic Synapses
por: Barak, Omri, et al.
Publicado: (2007) -
Neural Network Model of Memory Retrieval
por: Recanatesi, Stefano, et al.
Publicado: (2015) -
Spontaneous pattern generation by a network with dynamic synapses
por: Bibitchkov, Dmitri, et al.
Publicado: (2007) -
Neural network model of the primary visual cortex: From functional architecture to lateral connectivity and back
por: Blumenfeld, Barak, et al.
Publicado: (2006)