Abstract
This paper presents a set of evolutionary mechanisms embedded on an estimation of distribution algorithm (MITEDA-AC) that performs the synthesis of an analog low pass filter. Analog circuits are modeled with linked lists in order to represent and evolve both, topology and sizing. The developed representation mechanism ensures that generated circuits be feasible, and in order to reduce the gap between real circuits and those evolvable, the concept of preferred values was included on representation and generation mechanisms. The algorithm interacts with SPICE to performance evaluation of each individual in the population. MITEDA-AC was inspired by the COMIT because like this, it uses bivariate probability distributions to generate the optimal dependency tree, but without local optimizers. Features integrated in the learning mechanism of this evolvable algorithm, were the number of capacitors, resistors and inductors included in each circuit of the population. This paper describes the algorithm and discusses its results.
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Torres, A., Torres, M.D., de León, E.P. (2017). Automated Analog Synthesis with an Estimation of the Distribution Algorithm. In: Pichardo-Lagunas, O., Miranda-Jiménez, S. (eds) Advances in Soft Computing. MICAI 2016. Lecture Notes in Computer Science(), vol 10062. Springer, Cham. https://doi.org/10.1007/978-3-319-62428-0_14
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DOI: https://doi.org/10.1007/978-3-319-62428-0_14
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