Cargando…
Multimodal transistors as ReLU activation functions in physical neural network classifiers
Artificial neural networks (ANNs) providing sophisticated, power-efficient classification are finding their way into thin-film electronics. Thin-film technologies require robust, layout-efficient devices with facile manufacturability. Here, we show how the multimodal transistor’s (MMT’s) transfer ch...
Autores principales: | Surekcigil Pesch, Isin, Bestelink, Eva, de Sagazan, Olivier, Mehonic, Adnan, Sporea, Radu A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758690/ https://www.ncbi.nlm.nih.gov/pubmed/35027631 http://dx.doi.org/10.1038/s41598-021-04614-9 |
Ejemplares similares
-
Integrating geometries of ReLU feedforward neural networks
por: Liu, Yajing, et al.
Publicado: (2023) -
Improved Geometric Path Enumeration for Verifying ReLU Neural Networks
por: Bak, Stanley, et al.
Publicado: (2020) -
Training a Two-Layer ReLU Network Analytically
por: Barbu, Adrian
Publicado: (2023) -
A Cooperative Lightweight Translation Algorithm Combined with Sparse-ReLU
por: Xu, Xintao, et al.
Publicado: (2022) -
Studying the Evolution of Neural Activation Patterns During Training of Feed-Forward ReLU Networks
por: Hartmann, David, et al.
Publicado: (2021)