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Impact of designer knowledge in the interactive evolutionary optimisation of analogue CMOS ICs by using iMTGSPICE

Impact of designer knowledge in the interactive evolutionary optimisation of analogue CMOS ICs by using iMTGSPICE

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This Letter describes an innovative interactive evolutionary computational tool to optimise robust analogue complementary metal-oxide-semiconductor (CMOS) integrated circuits (ICs), by using genetic algorithm, entitled iMTGSPICE. The main results demonstrate that the iMTGSPICE is able to reduce the optimisation cycle times of designs of robust single-ended single-stage and Miller operational transconductance amplifiers (OTAs) in up to 93.9% in comparison to the non-interactive optimisation process. Moreover, the iMTGSPICE is capable of reducing the influence of the knowledge levels of the analogue CMOS ICs designers (experts and non-experts) to obtain robust potential solutions (maximum error of 0.5% for the Miller OTA).

References

    1. 1)
      • 1. Póvoa, R., Bastos, I., Lourenço, N., et al: ‘Automatic synthesis of RF front-end blocks using multi-objective evolutionary techniques’, Integr. VLSI J., 2016, 52, (1), pp. 243252, doi: https://doi.org/10.1016/j.vlsi.2015.04.005.
    2. 2)
    3. 3)
      • 3. Coello, C.A.C., Lamont, G.B., Veldhuizen, D.A.V.: ‘Evolutionary algorithms for solving multi-objective problems’ (Springer-Verlag, NY, 2007).
    4. 4)
      • 4. Moreto, R.A.L., Thomaz, C.E., Gimenez, S.P.: ‘Automatic optimization of robust analog CMOS ICs: an interactive genetic algorithm driven by human knowledge’. Proc. of the SBCCI 2018, Bento Gonçalves, Rio Grande do Sul, Brazil, August 2018.
    5. 5)
    6. 6)
      • 6. Zebulum, R.S., Pacheco, M.A., Vellasco, M.M.: ‘Evolutionary electronics: automatic design of electronic circuits and systems by genetic algorithms’ (CRC Press, EUA, 2002).
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