DOIONLINE 
DOIONLINE Publish In |
International Journal of Industrial Electronics and Electrical Engineering (IJIEEE)-IJIEEE |
 Journal Home Volume Issue |
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Issue |
Volume-7,Issue-2 ( Feb, 2019 ) | |||||||||
Paper Title |
Review of Spiking Neuron Models for Neuromorphic Hardware Implementation | |||||||||
Author Name |
Xiaoye Wang, Vishnu P. Nambiar, Wang Ling Goh, Anh Tuan Do | |||||||||
Affilition |
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore Institute of Microelectronics,Agency for Science, Technology and Research (A*STAR), Singapore, | |||||||||
Pages |
82-85 | |||||||||
Abstract |
Hardware implementation of spiking neural networks (SNN) has been the focus of many prior works [1-3] due to its relatively low power consumption. When building SNNs, it is typical to consider various forms of neuron models, as it is the key computational unit in the neural network. In this paper, various different digital neuron models will be introduced, followed by an analysis done on each of them, along with comparisons pertaining a series of different features they contain. Three methods of implementing LLIF on hardware will be looked at and comparisons will be made towards their respective components. Index Terms - Spiking Neuron Model, Spiking Neural Network Hardware, Digital Neuron Circuits. | |||||||||
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