Cargando…
Neural Network Training With Asymmetric Crosspoint Elements
Analog crossbar arrays comprising programmable non-volatile resistors are under intense investigation for acceleration of deep neural network training. However, the ubiquitous asymmetric conductance modulation of practical resistive devices critically degrades the classification performance of netwo...
Autores principales: | Onen, Murat, Gokmen, Tayfun, Todorov, Teodor K., Nowicki, Tomasz, del Alamo, Jesús A., Rozen, John, Haensch, Wilfried, Kim, Seyoung |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9124763/ https://www.ncbi.nlm.nih.gov/pubmed/35615470 http://dx.doi.org/10.3389/frai.2022.891624 |
Ejemplares similares
-
Enabling Training of Neural Networks on Noisy Hardware
por: Gokmen, Tayfun
Publicado: (2021) -
Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices
por: Gokmen, Tayfun, et al.
Publicado: (2017) -
Self-optimizing neural network in the classification of real valued data
por: Miniak-Górecka, Alicja, et al.
Publicado: (2022) -
Algorithm for Training Neural Networks on Resistive Device Arrays
por: Gokmen, Tayfun, et al.
Publicado: (2020) -
Adaptive neural PD controllers for mobile manipulator trajectory tracking
por: Hernandez-Barragan, Jesus, et al.
Publicado: (2021)