• DocumentCode
    704085
  • Title

    Empirical modelling of FDSOI CMOS inverter for signal/power integrity simulation

  • Author

    Dghais, Wael ; Rodriguez, Jonathan

  • Author_Institution
    Dept. of Electron., Univ. of Aveiro, Aveiro, Portugal
  • fYear
    2015
  • fDate
    9-13 March 2015
  • Firstpage
    1555
  • Lastpage
    1558
  • Abstract
    This paper presents a multiport empirical model based on artificial neural network for I/O memory interface (e.g. inverter) designed based on fully depleted silicon on isolator (FDSOI) CMOS 28 nm process for signal and power integrity assessments. The analog mixed-signal identification signals that carry the information about the I/O interface´s nonlinear dynamic behavior are recorded from large signal simulation setup. The model´s functions are extracted based on a nonlinear optimization algorithm and then implemented in Simulink software. The performance of the resulted model is validated in typical power and ground switching noise scenario. The developed empirical model accurately predicts the timing signal waveforms at the power, ground, and at the output port.
  • Keywords
    CMOS integrated circuits; integrated circuit design; integrated circuit modelling; invertors; mixed analogue-digital integrated circuits; silicon-on-insulator; FDSOI CMOS inverter; I/O memory interface; Simulink software; analog mixed-signal identification signals; artificial neural network; fully depleted silicon on isolator; multiport empirical model; nonlinear optimization algorithm; signal/power integrity simulation; size 28 nm; CMOS integrated circuits; Integrated circuit modeling; Inverters; Mathematical model; Predictive models; Semiconductor device modeling; Solid modeling; FDSOI CMOS inverter; large signal multiport model; signal and power integrity; transient analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design, Automation & Test in Europe Conference & Exhibition (DATE), 2015
  • Conference_Location
    Grenoble
  • Print_ISBN
    978-3-9815-3704-8
  • Type

    conf

  • Filename
    7092637