Cargando…
Synaptic transistor with multiple biological functions based on metal-organic frameworks combined with the LIF model of a spiking neural network to recognize temporal information
Spiking neural networks (SNNs) have immense potential due to their utilization of synaptic plasticity and ability to take advantage of temporal correlation and low power consumption. The leaky integration and firing (LIF) model and spike-timing-dependent plasticity (STDP) are the fundamental compone...
Autores principales: | Wang, Qinan, Zhao, Chun, Sun, Yi, Xu, Rongxuan, Li, Chenran, Wang, Chengbo, Liu, Wen, Gu, Jiangmin, Shi, Yingli, Yang, Li, Tu, Xin, Gao, Hao, Wen, Zhen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362020/ https://www.ncbi.nlm.nih.gov/pubmed/37484501 http://dx.doi.org/10.1038/s41378-023-00566-4 |
Ejemplares similares
-
Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks
por: Bi, Zedong, et al.
Publicado: (2016) -
Memristive LIF Spiking Neuron Model and Its Application in Morse Code
por: Fang, Xiaoyan, et al.
Publicado: (2022) -
Spatio-temporal pattern recognizers using spiking neurons and spike-timing-dependent plasticity
por: Humble, James, et al.
Publicado: (2012) -
STSC-SNN: Spatio-Temporal Synaptic Connection with temporal convolution and attention for spiking neural networks
por: Yu, Chengting, et al.
Publicado: (2022) -
Scaling of temporal correlations in densely connected networks of LIF neurons
por: Manrique, Jesús, et al.
Publicado: (2011)