Effect of conductance linearity and multi-level cell characteristics of TaOx-based synapse device on pattern recognition accuracy of neuromorphic system
SCIE
SCOPUS
- Title
- Effect of conductance linearity and multi-level cell characteristics of TaOx-based synapse device on pattern recognition accuracy of neuromorphic system
- Authors
- Sung, Changhyuck; Lim, Seokjae; Kim, Hyungjun; Kim, Taesu; Moon, Kibong; Song, Jeonghwan; Kim, Jae-Joon; Hwang, Hyunsang
- Date Issued
- 2018-03
- Publisher
- IOP PUBLISHING LTD
- Abstract
- To improve the classification accuracy of an image data set (CIFAR-10) by using analog input voltage, synapse devices with excellent conductance linearity (CL) and multi-level cell (MLC) characteristics are required. We analyze the CL and MLC characteristics of TaOx-based filamentary resistive random access memory (RRAM) to implement the synapse device in neural network hardware. Our findings show that the number of oxygen vacancies in the filament constriction region of the RRAM directly controls the CL and MLC characteristics. By adopting a Ta electrode (instead of Ti) and the hot-forming step, we could form a dense conductive filament. As a result, a wide range of conductance levels with CL is achieved and significantly improved image classification accuracy is confirmed.
- Keywords
- Classification (of information); Image classification; Image enhancement; Oxygen vacancies; Pattern recognition; Pattern recognition systems; RRAM; Tantalum compounds; Classification accuracy; Multi level cell (MLC); Neural network hardware; Neuromorphic systems; Pattern Recognition accuracies; Resistive random access memory (rram); synapse device; TaOx; Random access storage
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/94605
- DOI
- 10.1088/1361-6528/aaa733
- ISSN
- 0957-4484
- Article Type
- Article
- Citation
- NANOTECHNOLOGY, vol. 29, no. 11, 2018-03
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- There are no files associated with this item.
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