A current-mode conductance-based silicon neuron for Address-Event neuromorphic systems

被引：87

作者：

Livi, Paolo ^{[1
]}

Indiveri, Giacomo ^{[2
]}

机构：

[1] Swiss Fed Inst Technol, Bio Engn Lab, Dept Biosyst Sci & Engn BSSE, Mattenstr 26, CH-4058 Basel, Switzerland

[2] Univ Zurich, ETH Zurich, Inst Neuroinformat, CH-8057 Zurich, Switzerland

来源：

ISCAS: 2009 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1-5 | 2009年

关键词：

SPIKING; DYNAMICS;

D O I：

10.1109/ISCAS.2009.5118408

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Silicon neuron circuits emulate the electro-physiological behavior of real neurons. Many circuits can be integrated on a single Very Large Scale Integration (VLSI) device, and form large networks of spiking neurons. Connectivity among neurons can be achieved by using time multiplexing and fast asynchronous digital circuits. As the basic characteristics of the silicon neurons are determined at design time, and cannot be changed after the chip is fabricated, it is crucial to implement a circuit which represents an accurate model of real neurons, but at the same time is compact, low-power and compatible with asynchronous logic. Here we present a current-mode conductance. based neuron circuit, with spike-frequency adaptation, refractory period, and bio-physically realistic dynamics which is compact, low-power and compatible with fast asynchronous digital circuits.

引用

页码：2898 / +

页数：2

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