We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Open-loop analog programmable electrochemical memory array.
- Authors
Chen, Peng; Liu, Fenghao; Lin, Peng; Li, Peihong; Xiao, Yu; Zhang, Bihua; Pan, Gang
- Abstract
Emerging memories have been developed as new physical infrastructures for hosting neural networks owing to their low-power analog computing characteristics. However, accurately and efficiently programming devices in an analog-valued array is still largely limited by the intrinsic physical non-idealities of the devices, thus hampering their applications in in-situ training of neural networks. Here, we demonstrate a passive electrochemical memory (ECRAM) array with many important characteristics necessary for accurate analog programming. Different image patterns can be open-loop and serially programmed into our ECRAM array, achieving high programming accuracies without any feedback adjustments. The excellent open-loop analog programmability has led us to in-situ train a bilayer neural network and reached software-like classification accuracy of 99.4% to detect poisonous mushrooms. The training capability is further studied in simulation for large-scale neural networks such as VGG-8. Our results present a new solution for implementing learning functions in an artificial intelligence hardware using emerging memories. Memory devices with open-loop analog programmability are highly desired in training tasks. Here, the authors developed an electrochemical memory array that can be accurately programmed without any feedback, offering unique capabilities for training.
- Subjects
ARTIFICIAL intelligence; MEMORY
- Publication
Nature Communications, 2023, Vol 14, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-023-41958-4