神经形态工程学
仿真
记忆电阻器
计算机科学
电阻随机存取存储器
计算机体系结构
非常规计算
油藏计算
非易失性存储器
纳米技术
电气工程
材料科学
分布式计算
工程类
人工神经网络
计算机硬件
人工智能
电压
循环神经网络
经济
经济增长
作者
Haider Abbas,Jiayi Li,D. S. Ang
出处
期刊:Micromachines
[Multidisciplinary Digital Publishing Institute]
日期:2022-04-30
卷期号:13 (5): 725-725
被引量:43
摘要
Due to a rapid increase in the amount of data, there is a huge demand for the development of new memory technologies as well as emerging computing systems for high-density memory storage and efficient computing. As the conventional transistor-based storage devices and computing systems are approaching their scaling and technical limits, extensive research on emerging technologies is becoming more and more important. Among other emerging technologies, CBRAM offers excellent opportunities for future memory and neuromorphic computing applications. The principles of the CBRAM are explored in depth in this review, including the materials and issues associated with various materials, as well as the basic switching mechanisms. Furthermore, the opportunities that CBRAMs provide for memory and brain-inspired neuromorphic computing applications, as well as the challenges that CBRAMs confront in those applications, are thoroughly discussed. The emulation of biological synapses and neurons using CBRAM devices fabricated with various switching materials and device engineering and material innovation approaches are examined in depth.
科研通智能强力驱动
Strongly Powered by AbleSci AI