Abstract
Three-dimensional environmentally sustainable neuromorphic computing system based on natural organic honey-memristor is proposed in this paper. The experimental results indicate the proposed systems have high inference accuracy over 90 % with device variation and nonlinearity. What is more, four conductance drift scenarios, ADC (Analog-to-Digital Converter) quantization effects, and different algorithms (VGG8 and DenseNet-40) are considered to further verify the proposed systems.
Recommended Citation
J. Wang et al., "Three-dimensional Environmentally Sustainable Neuromorphic Computing System based on Natural Organic Memristor," Midwest Symposium on Circuits and Systems, pp. 182 - 186, Institute of Electrical and Electronics Engineers, Jan 2023.
The definitive version is available at https://doi.org/10.1109/MWSCAS57524.2023.10406015
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
artificial intelligence (AI); honey-memristor; inference ac-curacy; Natural organic memristor; neuromorphic system; nonlinearity; three-dimensional (3D); variation
International Standard Serial Number (ISSN)
1548-3746
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2023
Comments
National Science Foundation, Grant 2104976