CMOS and Memristive Hardware for Neuromorphic Computing
been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/aisy.201900189. This article is protected by copyright. All rights reserved CMOS and Memristive Hardware for Neuromorphic Computing Mostafa Rahimi Azghadi, Ying-Chen Chen, Jason K. Eshraghian, Jia Chen, Chih-Yang Lin, Amirali Amirsoleimani, Adnan Mehonic, Anthony J Kenyon, Burt Fowler, Jack C Lee, Yao-Feng Chang College of Science and Engineering, James Cook University, Townsville, QLD 4811, Australia Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712, United States Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, MI 48109-2122, United States Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada Department of Electronic and Electrical Engineering, University College London, Torrington Place, London, United Kingdom mostafa.rahimiazghadi@jcu.edu.au, yfchang@utexas.edu ABSTRACT The ever-increasing processing power demands of digital computers cannot continue to be fulfilled indefinitely unless there is a paradigm shift in computing. Neuromorphic computing, which takes A cc ep te d A rti cl e