Parallel Hybrid Evolutionary Algorithm based on Chaos-GA-PSO for SPICE Model Parameter Extraction

被引:5
|
作者
Wu, Yuping [1 ]
机构
[1] Chinese Acad Sci, Inst Microelect, Beijing, Peoples R China
关键词
SPICE model; parameter extraction; parallel global optimization; generic alorithm (GA); particle swarm optimization (PSO); Message Passing Interface (MPI); PARTICLE; OPTIMIZATION;
D O I
10.1109/ICICISYS.2009.5357768
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
SPICE model is one of the key technical connections between the integrated-circuit technology community and the design community Design community requires accurate SPICE model parameters so as to make the difference between design spec and practical spec minimized as possible To get accurate model parameters, optimization algorithms are used for parameter extraction A parallel hybrid evolutionary algorithm based chaos-GA-PSO is presented for SPICE model parameter extraction, which gets leverage of the advantages from chaos algorithm, genetic algorithm, and particle swarm optimization, overcomes their respective disadvantages, passes good individuals among them, avoids local area optimization efficiently, and gets more accurate global optimized parameter extraction results Also such algorithm based SPICE model parameter extraction architecture is presented with model convergence checking and derivate ability checking supported
引用
收藏
页码:688 / 692
页数:5
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