Cargando…
Generalised Analog LSTMs Recurrent Modules for Neural Computing
The human brain can be considered as a complex dynamic and recurrent neural network. There are several models for neural networks of the human brain, that cover sensory to cortical information processing. Large majority models include feedback mechanisms that are hard to formalise to realistic appli...
Autores principales: | Adam, Kazybek, Smagulova, Kamilya, James, Alex |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506007/ https://www.ncbi.nlm.nih.gov/pubmed/34650420 http://dx.doi.org/10.3389/fncom.2021.705050 |
Ejemplares similares
-
Child-Sum EATree-LSTMs: enhanced attentive Child-Sum Tree-LSTMs for biomedical event extraction
por: Wang, Lei, et al.
Publicado: (2023) -
Short-term solar energy forecasting: Integrated computational intelligence of LSTMs and GRU
por: Zameer, Aneela, et al.
Publicado: (2023) -
Forecasting Hazard Level of Air Pollutants Using LSTM’s
por: Gul, Saba, et al.
Publicado: (2020) -
Anomaly Detection Using an Ensemble of Multi-Point LSTMs
por: Lee, Geonseok, et al.
Publicado: (2023) -
Exploring Musical Structure Using Tonnetz Lattice Geometry and LSTMs
por: Aminian, Manuchehr, et al.
Publicado: (2020)