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A Hybrid Technique for TCAD Modeling and Optimization

  • B. Govoreanu
  • J. Kopalides
  • W. Schoenmaker
  • G. Dima
  • O. Mitrea
  • M. D. Profirescu
Conference paper

Abstract

This paper focuses on continuous simulated annealing global optimization method to be used in conjunction with statistical response surface modeling and powerful local optimization techniques to improve the design and analysis using TCAD.

Keywords

Simulated Annealing Response Surface Modeling Radial Basis Function Probability Density Estimate Local Optimization Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    J. Sacks et al “Design of Computer Experiments” Statistical Science, vol. 4, PP. 409–435, 1996 MathSciNetCrossRefGoogle Scholar
  2. [2]
    W. Schoenmaker, R. Cartuyvels “Theory and Implementation of a New Interpolation Method Based on Random Sampling” IEEE J. of TCAD 1997 URL address: http://t cad. Stanford, edu/tcad-journal/archive/ Google Scholar
  3. [3]
    L. Ingber “Simulated Annealing: Practice versus Theory” J. Mathl. Comput. Modeling, vol. 18, pp. 29–57, 1993 MATHMathSciNetCrossRefGoogle Scholar
  4. [4]
    E.H.L. Aarts, P.M.J. van Laarhoven “Simulated Annealing: Theory and Applications” Kluwer Ac. Publ, 1987 MATHGoogle Scholar
  5. [5]
    T. Poggio, F. Girossi “Networks for Approximation and Learning” Proceedings of IEEE, 1990, vol. 78, no. 9, pp. 1481–1496 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag/Wien 1998

Authors and Affiliations

  • B. Govoreanu
    • 1
    • 2
  • J. Kopalides
    • 2
  • W. Schoenmaker
    • 2
  • G. Dima
    • 1
  • O. Mitrea
    • 1
  • M. D. Profirescu
    • 1
  1. 1.Technical University of BucharestBucharest 6Romania
  2. 2.ASP DivisionIMECLeuvenBelgium

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