Fast numerical integration of relaxation oscillator networks based on singular limit solutions

被引:26
作者
Linsay, PS
Wang, DLL
机构
[1] MIT, Ctr Plasma Fus, Cambridge, MA 02139 USA
[2] Ohio State Univ, Dept Comp & Informat Sci, Columbus, OH 43210 USA
[3] Ohio State Univ, Ctr Cognit Sci, Columbus, OH 43210 USA
来源
IEEE TRANSACTIONS ON NEURAL NETWORKS | 1998年 / 9卷 / 03期
基金
美国国家科学基金会;
关键词
LEGION; neural networks; numerical integration; relaxation oscillators; singular limit method;
D O I
10.1109/72.668894
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Relaxation oscillations exhibiting more than one time scale arise naturally from many physical systems. When relaxation oscillators are coupled in a way that resembles chemical synapses, we propose a fast method to numerically integrate such networks. The numerical technique, called the singular limit method, is derived from analysis of relaxation oscillations in the singular limit. In such limit, system evolution gives rise to time instants at which fast dynamics takes place and intervals between them during which slow dynamics takes place. A full description of the method is given for a locally excitatory globally inhibitory oscillator network (LEGION), where fast dynamics, characterized by jumping which leads to dramatic phase shifts, is captured in this method by iterative operation and slow dynamics is entirely solved. The singular limit method is evaluated by computer experiments, and it produces remarkable speedup compared to other methods of integrating these systems. The speedup makes it possible to simulate large-scale oscillator networks.
引用
收藏
页码:523 / 532
页数:10
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