• DocumentCode
    2064369
  • Title

    Sparse basis pursuit on automatic nonlinear circuit modeling

  • Author

    Yu-Chung Hsiao ; Daniel, Luca

  • Author_Institution
    Electr. Eng. & Comput. Sci., Massachusetts Inst. of Technol., Cambridge, MA, USA
  • fYear
    2013
  • fDate
    28-31 Oct. 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, we propose a black-box nonlinear dynamic modeling algorithm that automatically selects essential basis functions to overcome the overfitting problem. Our automatic modeling algorithm, which is formulated as a convex optimization problem, guarantees model stability in transient simulation. Furthermore, we incorporate our algorithm with a sparsity induction mechanism, which improves model robustness and generalization capabilities, as shown in our example.
  • Keywords
    convex programming; nonlinear dynamical systems; nonlinear network synthesis; automatic modeling algorithm; automatic nonlinear circuit modeling; basis functions; black-box nonlinear dynamic modeling algorithm; convex optimization problem; model stability; overfitting problem; sparse basis pursuit; sparsity induction mechanism; transient simulation; Abstracts; Measurement uncertainty; Object recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    ASIC (ASICON), 2013 IEEE 10th International Conference on
  • Conference_Location
    Shenzhen
  • ISSN
    2162-7541
  • Print_ISBN
    978-1-4673-6415-7
  • Type

    conf

  • DOI
    10.1109/ASICON.2013.6811858
  • Filename
    6811858