Journal of Global Optimization
Proceedings of the 2005 Asia and South Pacific Design Automation Conference
Parallel genetic algorithm for SPICE model parameter extraction
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Chassis: A Platform for Verifying PMU Integration Using Autogenerated Behavioral Models
ACM Transactions on Design Automation of Electronic Systems (TODAES)
A differential memetic algorithm
Artificial Intelligence Review
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This paper provides an effective method for parameter extraction of microelectronic devices and elements. A novel method, memetic differential evolution (MDE) algorithm, is proposed in this paper. By combining differential evolution (DE) algorithm, mutations in immune algorithm (IA), and special operators for parameter extraction, MDE possesses characteristics of high accuracy, stability, generality, and efficiency. The effectiveness of the method has been shown by two typical examples, including small-signal equivalent circuit models for an AlGaN/GaN HEMT device up to 40GHz, as well as an equivalent circuit model for on-chip differential spiral inductors. In both cases, the initial values and parameter ranges of the elements in the equivalent circuits are hard to determine in optimization. The results and comparisons with Levenberg-Marquardt (LM) algorithm, genetic algorithm (GA), particle swarm optimization (PSO) algorithm and canonical DE algorithm, demonstrate the superiority of MDE in terms of accuracy and generality.