Journal ArticleDOI
Bridging Biological and Artificial Neural Networks with Emerging Neuromorphic Devices: Fundamentals, Progress, and Challenges.
Jianshi Tang,Fang Yuan,Xinke Shen,Zhongrui Wang,Mingyi Rao,Yuanyuan He,Yuhao Sun,Xinyi Li,Wenbin Zhang,Yijun Li,Bin Gao,He Qian,Guo-Qiang Bi,Sen Song,Jianhua Yang,Huaqiang Wu +15 more
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TLDR
A systematic overview of biological and artificial neural systems is given, along with their related critical mechanisms, and the existing challenges are highlighted to hopefully shed light on future research directions.Abstract:
As the research on artificial intelligence booms, there is broad interest in brain-inspired computing using novel neuromorphic devices. The potential of various emerging materials and devices for neuromorphic computing has attracted extensive research efforts, leading to a large number of publications. Going forward, in order to better emulate the brain's functions, its relevant fundamentals, working mechanisms, and resultant behaviors need to be re-visited, better understood, and connected to electronics. A systematic overview of biological and artificial neural systems is given, along with their related critical mechanisms. Recent progress in neuromorphic devices is reviewed and, more importantly, the existing challenges are highlighted to hopefully shed light on future research directions.read more
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Journal ArticleDOI
Two-dimensional materials for next-generation computing technologies.
Chunsen Liu,Huawei Chen,Shuiyuan Wang,Qi Liu,Qi Liu,Yu-Gang Jiang,David Wei Zhang,Ming Liu,Ming Liu,Peng Zhou +9 more
TL;DR: The opportunities, progress and challenges of integrating two-dimensional materials with in-memory computing and transistor-based computing technologies, from the perspective of matrix and logic computing, are discussed.
Journal ArticleDOI
Brain-inspired computing with memristors: Challenges in devices, circuits, and systems
Yang Zhang,Yang Zhang,Zhongrui Wang,Jiadi Zhu,Yuchao Yang,Mingyi Rao,Wenhao Song,Ye Zhuo,Xumeng Zhang,Xumeng Zhang,Menglin Cui,Linlin Shen,Ru Huang,Jianhua Yang +13 more
TL;DR: This article provides a review of current development and challenges in brain-inspired computing with memristors and survey the progress of memristive spiking and artificial neural networks.
Journal ArticleDOI
Semiconductor Quantum Dots for Memories and Neuromorphic Computing Systems
TL;DR: This work focuses on the development of nonvolatile memories and neuromorphic computing systems based on QD thin-film solids and discusses the advantageous traits of QDs for novel and optimized memory techniques in both conventional flash memories and emerging memristors.
Journal ArticleDOI
Emerging Memristive Artificial Synapses and Neurons for Energy-Efficient Neuromorphic Computing.
TL;DR: A wide range of memristors and memristive-related devices for artificial synapses and neurons is highlighted and the device structures, switching principles, and the applications of essential synaptic and neuronal functionalities are sequentially presented.
Journal ArticleDOI
Dynamic memristor-based reservoir computing for high-efficiency temporal signal processing.
TL;DR: In this paper, a parallel dynamic memristor-based reservoir computing system was proposed by applying a controllable mask process, in which the critical parameters, including state richness, feedback strength and input scaling, can be tuned by changing the mask length and the range of input signal.
References
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Paul A. Merolla,John V. Arthur,Rodrigo Alvarez-Icaza,Andrew S. Cassidy,Jun Sawada,Filipp Akopyan,Bryan L. Jackson,Nabil Imam,Chen Guo,Yutaka Nakamura,Bernard Brezzo,Ivan Vo,Steven K. Esser,Rathinakumar Appuswamy,Brian Taba,Arnon Amir,Myron D. Flickner,William P. Risk,Rajit Manohar,Dharmendra S. Modha +19 more