Dynamical Digital Silicon Neurons

被引：43

作者：

Cassidy, Andrew ^{[1
]}

Andreou, Andreas G. ^{[1
]}

机构：

[1] Johns Hopkins Univ, Dept Elect & Comp Engn, Baltimore, MD 21218 USA

来源：

2008 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE - INTELLIGENT BIOMEDICAL SYSTEMS (BIOCAS) | 2008年

关键词：

D O I：

10.1109/BIOCAS.2008.4696931

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present an array of dynamical digital silicon neurons implementing the Izhikevich neuron model [1]. The FPGA based array consists of 32 physical neurons, each time multiplexing the state of 8 virtual neurons, for a total of 256 independent neurons. The neural array operates at 5,000 times faster than real time, performing over 20.48 GOPS (Giga Operations Per Second). It is intended for neural simulation acceleration, neural prostheses, and neuromorphic systems,

引用

页码：289 / 292

页数：4

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