期刊
FRONTIERS IN NEUROSCIENCE
卷 5, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fnins.2011.00073
关键词
analog VLSI; subthreshold; spiking; integrate and fire; conductance based; adaptive exponential; log-domain; circuit
资金
- EU ERC [257219]
- EU ICT [231467, 216777, 231168, 15879]
- Swiss National Science Foundation [119973]
- UK EPSRC [EP/C010841/1]
- Spanish grants [TEC2006-11730-C03-01, TEC2009-10639-C04-01, P06TIC01417]
- Australian Research Council [DP0343654, DP0881219]
- European Regional Development Fund
- Engineering and Physical Sciences Research Council [EP/C010841/1] Funding Source: researchfish
Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain-machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance-based Hodgkin-Huxley models to bi-dimensional generalized adaptive integrate and fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据