Artificial Working Memory Constructed by Planar 2D Channel Memristors Enabling Brain‐Inspired Hierarchical Memory Systems. (7th October 2021)

• Record Type: Journal Article
• Authors: Ji, Xinglong; Hao, Song; Lim, Kian Guan; Zhong, Shuai; Zhao, Rong
• Is Part Of: Advanced intelligent systems. Volume 4:Number 3(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-10-07
• Subjects: artificial working memory -- brain-inspired hierarchical memory -- planar 2D channel memristors -- short-term synapses; Artificial intelligence -- Periodicals; Robotics -- Periodicals; Control theory -- Periodicals; 006.3
• DOI: 10.1002/aisy.202100119
• Languages: English
• ISSNs: 2640-4567

Abstract

Abstract : In human hierarchical memory structures, working memory functions as a temporal interface to integrate multimodal information from sensory memory and long‐term memory, underpinning cognition development. Therefore, an artificial working memory is highly anticipated to endow computing systems with advanced capabilities. Herein, an artificial working memory that can synthesize and process multimodal information to enable a brain‐inspired hierarchical memory system is developed. To emulate the characteristic synaptic behavior of working memory, a planar 2D channel memristor (PTCM) with stable short‐term frequency‐dependent plasticity is designed. An array of PTCMs on a monolayer MoS2 grain are assembled and the information encoding, forgetting, retrieval, and updating functions of working memory are experimentally demonstrated. A hierarchical memory system through simulation, which integrates working memory network, sensory memory, and long‐term memory, is built, emulating the information synthesizing and processing procedures of the human brain. The proposed system provides a promising way to enhance the cognitive capability of intelligence machines. Abstract : In human hierarchical memory structure, working memory functions as a temporal interface to integrate multimodal information, underpinning the cognition development. Herein, an artificial working memory that can synthesize and process multimodal information is developed, emulating the information processing procedures in human brain, which provides a promising way to enhance the cognitive capability of intelligence systems.