• DocumentCode
    956022
  • Title

    OPTIMA: A nonlinear model parameter extraction program with statistical confidence region algorithms

  • Author

    Sharma, Mahesh S. ; Arora, Narain D.

  • Author_Institution
    Digital Equipment Corp., Hudson, MA, USA
  • Volume
    12
  • Issue
    7
  • fYear
    1993
  • fDate
    7/1/1993 12:00:00 AM
  • Firstpage
    982
  • Lastpage
    987
  • Abstract
    A device model parameter optimization program, OPTIMA, for extracting parameter values of empirical and/or analytical models most commonly used for VLSI circuit simulation, is described. Such device models often have parameters which are correlated, and some of them could be redundant. OPTIMA can automatically detect redundant model parameter combinations. This not only allows one to extract more meaningful parameters, but also helps in the development of improved physical models with a minimum number of empirical parameters. The parameter redundancy is detected using a statistical confidence region algorithm which can be implemented as a postprocessor to any gradient-based least-squares optimization method. The advantage of the statistical confidence region algorithm in OPTIMA, as applied to MOSFET model parameter extraction, is discussed, using examples from drain and substrate current modeling
  • Keywords
    MOS integrated circuits; VLSI; circuit CAD; digital simulation; insulated gate field effect transistors; redundancy; semiconductor device models; MOSFET; OPTIMA; VLSI circuit simulation; gradient-based least-squares optimization method; nonlinear model parameter extraction program; parameter values; physical models; redundant model parameter combinations; statistical confidence region algorithm; Analytical models; Circuit simulation; Constraint optimization; Curve fitting; Geometry; Least squares methods; MOSFET circuits; Parameter extraction; Solid modeling; Very large scale integration;
  • fLanguage
    English
  • Journal_Title
    Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0070
  • Type

    jour

  • DOI
    10.1109/43.238034
  • Filename
    238034