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A method to data-mine results of an analog circuit sizing in order to extract knowledge that can be immediately used by designers or students of analog integrated circuit design is presented. The symbolic models, which have been generated using multi-objective genetic programming, are human-interpretable mathematical models. The procedure presented involves two steps: the generation of samples of Pareto-optimal performance sizes of two unity gain cells using the NSGA-II genetic algorithm; and the generation of models of each of the objectives sized by symbolic regression via genetic programming. The functionality of the method to describe circuits is shown in three cases: two current followers and one voltage follower.

Modelado simbólico del conjunto Óptimo de Pareto de dos celdas de ganancia unitaria