An Efficient Kriging-based Constrained Multi-objective Evolutionary Algorithm for Analog Circuit Synthesis via Self-adaptive Incremental Learning

2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)(2022)

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摘要
In this paper, we propose an efficient Kriging-based constrained multi-objective evolutionary algorithm for analog circuit synthesis via self-adaptive incremental learning. The incremental learning technique is introduced to reduce time complexity of training the Kriging model from $O(n^{3})$, to $O(n^{2})$, where $n$ is the number of training points. The proposed ...
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关键词
Training,Design automation,Evolutionary computation,Analog circuits,Predictive models,Bayes methods,Integrated circuit modeling
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