Simulation of spiking neural networks -: architectures and implementations

被引:27
作者
Schæfer, M
Schoenauer, T
Wolff, C [1 ]
Hartmann, G
Klar, H
Rückert, U
机构
[1] Univ Paderborn, Heinz Nixdorf Inst, D-33102 Paderborn, Germany
[2] Tech Univ Berlin, Inst Microelect & Solid State Elect, D-10587 Berlin, Germany
关键词
spiking neural networks; PCNN simulation; accelerators; vision networks;
D O I
10.1016/S0925-2312(01)00633-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The fast simulation of large networks of spiking neurons is a major task for the examination of biology-inspired vision systems. Networks of this type label features by synchronization of spikes and there is strong demand to simulate these effects in real world environments. As the calculations for one model neuron are complex, the digital simulation of large networks is not efficient using existing simulation systems. Consequently, it is necessary to develop special simulation techniques. This article introduces a wide range of concepts for the different parts of digital simulator systems for large vision networks and presents accelerators based on these foundations. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:647 / 679
页数:33
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