A Survey of Neuromorphic Computing Based on Spiking Neural Networks

ZHANG Ming; GU Zonghua; PAN Gang

doi:10.1049/cje.2018.05.006

Volume 27 Issue 4

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ZHANG Ming, GU Zonghua, PAN Gang, “A Survey of Neuromorphic Computing Based on Spiking Neural Networks,” Chinese Journal of Electronics, vol. 27, no. 4, pp. 667-674, 2018, doi: 10.1049/cje.2018.05.006

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ZHANG Ming, GU Zonghua, PAN Gang, “A Survey of Neuromorphic Computing Based on Spiking Neural Networks,” Chinese Journal of Electronics, vol. 27, no. 4, pp. 667-674, 2018, doi: 10.1049/cje.2018.05.006

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A Survey of Neuromorphic Computing Based on Spiking Neural Networks

doi: 10.1049/cje.2018.05.006

School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China

Funds: This work is supported by National Key Basic Research and Development Program of China (No.2017YFB1002503) and the National Natural Science Foundation of China (No.61672454).

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Corresponding author: GU Zonghua (corresponding author) received the Ph.D. degree in computer science and engineering from the University of Michigan at Ann Arbor in 2004. He is currently an associate professor in the College of Computer Science, Zhejiang University. (Email:zonghua@gmail.com)
Received Date: 2017-03-14
Rev Recd Date: 2017-07-04
Publish Date: 2018-07-10

Abstract

Abstract

Neuromorphic computing aims to build digital or analog computer systems that emulate or simulate the biological brain, in order to achieve high performance and low power consumption for intelligent information processing applications. This article reviews on neuromorphic computing based on Spiking neural networks (SNNs), including its history of development, common neuron models, major research projects, neuromorphic sensors, and applications in brain-computer Interfaces.
- Neuromorphic computing,
- Spiking neural networks,
- Brain-inspired computing,
- Machine learning

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