A High-Precision Implementation of the Sigmoid Activation Function for Computing-in-Memory Architecture

Computing-In-Memory (CIM), based on non-von Neumann architecture, has lately received significant attention due to its lower overhead in delay and higher energy efficiency in convolutional and fully-connected neural network computing. Growing works have given the priority to researching the array of...

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Detalles Bibliográficos
Autores principales: Xu, Siqiu, Li, Xi, Xie, Chenchen, Chen, Houpeng, Chen, Cheng, Song, Zhitang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8540118/
https://www.ncbi.nlm.nih.gov/pubmed/34683234
http://dx.doi.org/10.3390/mi12101183

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8540118/
https://www.ncbi.nlm.nih.gov/pubmed/34683234
http://dx.doi.org/10.3390/mi12101183

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