神经形态工程学
计算机科学
尖峰神经网络
Spike(软件开发)
计算机体系结构
适应性
高效能源利用
人工神经网络
非易失性存储器
分布式计算
人工智能
工程类
电气工程
计算机硬件
生物
软件工程
生态学
作者
M. Lakshmi Varshika,Federico Corradi,Anup Das
出处
期刊:Electronics
[Multidisciplinary Digital Publishing Institute]
日期:2022-05-18
卷期号:11 (10): 1610-1610
被引量:31
标识
DOI:10.3390/electronics11101610
摘要
A sustainable computing scenario demands more energy-efficient processors. Neuromorphic systems mimic biological functions by employing spiking neural networks for achieving brain-like efficiency, speed, adaptability, and intelligence. Current trends in neuromorphic technologies address the challenges of investigating novel materials, systems, and architectures for enabling high-integration and extreme low-power brain-inspired computing. This review collects the most recent trends in exploiting the physical properties of nonvolatile memory technologies for implementing efficient in-memory and in-device computing with spike-based neuromorphic architectures.
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