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	Energy-Efficient Bio-Mimic Silicon Neuron and STDP Synapse for Analogue Neuromorphic VLSI
	Jinyong Zhang; Shing-Chow Chan; Hui Li; Nannan Zhang; Lei Wang
	2017
会议日期	2017
会议地点	德国
英文摘要	Brain is able to process sophisticated information, to handle high computational throughput and to make decisions while consuming less energy with smaller size in comparison with the current Von Neumann system. Building VLSI brain-like systems in silicon draws growing interest in recent years [1, 2]. However, the main challenges of these systems are large dimension and low computationally efficient as well as energy-wasting. The analog implementation is considered as a more promising solution for future neuromorphic VLSI sy
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/12202]
专题	深圳先进技术研究院_医工所
作者单位	2017
推荐引用方式 GB/T 7714	Jinyong Zhang,Shing-Chow Chan,Hui Li,et al. Energy-Efficient Bio-Mimic Silicon Neuron and STDP Synapse for Analogue Neuromorphic VLSI[C]. 见:. 德国. 2017.

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