Associative Memory for Image Recovery with a High‐Performance Memristor Array. (12th April 2019)

• Record Type: Journal Article
• Authors: Zhou, Ying; Wu, Huaqiang; Gao, Bin; Wu, Wei; Xi, Yue; Yao, Peng; Zhang, Shuanglin; Zhang, Qingtian; Qian, He
• Is Part Of: Advanced functional materials. Volume 29:Number 30(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-04-12
• Subjects: associative memory -- memristor -- neuromorphic computing; Materials -- Periodicals; Chemical vapor deposition -- Periodicals; 620.11
• DOI: 10.1002/adfm.201900155
• Languages: English
• ISSNs: 1616-301X

Abstract

Abstract: Associative memory is one of the significant characteristics of the biological brain. However, it has yet to be realized in a large memristor array due to the high requirements on the memristor device. In this work, the multilevel memristor cell is optimized by employing an electro‐thermal modulation layer. Memristor devices show both high resistance, cell‐to‐cell uniformity, and multilevel resistive switching behaviors with good reliability. A Hopfield neural network is experimentally demonstrated on a 1k memristor array that is capable of realizing the associative memory function for emotion image recovery. By using both asynchronous and synchronous refresh schemes, complete emotion images can be recalled from partial information. Abstract : In this work, a multilevel memristor cell is optimized by employing an electro‐thermal modulation layer. Memristor devices show both high resistance, cell‐to‐cell uniformity, and multilevel resistive switching behaviors with good reliability. A Hopfield neural network is experimentally demonstrated on a 1k memristor array that can realize the associative memory function for emotion images recovery.