Energy-Efficient Bio-Mimic Silicon Neuron and STDP Synapse for Analogue Neuromorphic VLSI
文献类型：会议论文
| 作者 | Jinyong Zhang; Shing-Chow Chan; Hui Li; Nannan Zhang; Lei Wang |
| 出版日期 | 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 |
| 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. |
入库方式： OAI收割
来源：深圳先进技术研究院
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