• DocumentCode
    446092
  • Title

    Modeling of spiral inductors using artificial neural network

  • Author

    Liu, Tao ; Zhang, Wenjun ; Yu, Zhiping

  • Author_Institution
    Inst. of Microelectron., Tsinghua Univ., Beijing, China
  • Volume
    4
  • fYear
    2005
  • fDate
    July 31 2005-Aug. 4 2005
  • Firstpage
    2353
  • Abstract
    A new model for spiral inductors, which covers wide operation frequency range and full design parameters, is proposed by using artificial neural network (ANN). It is pointed out that a four-layered neural network is superior to a three-layered neural network both on the mapping and generalization abilities in spiral inductor modeling. For the first time, a novel physics-based sampling technique is adopted in modeling procedure. Equipped with this new sampling method, ANN model achieves better speed and accuracy performances though the training data are substantially reduced. The new sampling method can be easily applied to other passive components and be embedded in various modeling frameworks.
  • Keywords
    artificial intelligence; circuit CAD; inductors; neural nets; sampling methods; artificial neural network; circuit design; physics based sampling technique; spiral inductors; Artificial neural networks; Circuits; Design automation; Inductors; Neural networks; Radio frequency; Sampling methods; Scattering parameters; Spirals; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
  • Conference_Location
    Montreal, Que.
  • Print_ISBN
    0-7803-9048-2
  • Type

    conf

  • DOI
    10.1109/IJCNN.2005.1556269
  • Filename
    1556269