• DocumentCode
    2686474
  • Title

    USB3.1 silicon and channel design optimization using artificial neural network modeling

  • Author

    Mo Liu ; Tsai, Jennifer Hsiao-Ping

  • Author_Institution
    Platform Eng. Group, Intel Corp., Santa Clara, CA, USA
  • fYear
    2015
  • fDate
    15-21 March 2015
  • Firstpage
    289
  • Lastpage
    293
  • Abstract
    This paper adopts neural network modeling for USB3.1 Gen 2 high speed signal channel simulation instead of conventional response surface methodology. The paper demonstrates the co-design and optimization flow of USB3.1 silicon and channel parameters and how neural network modeling captures the complex response in a wide range with high accuracy.
  • Keywords
    neural nets; signal processing; USB3.1 silicon; artificial neural network modeling; channel design optimization; channel parameters; high speed signal channel simulation; response surface methodology; Biological neural networks; Fitting; Impedance; Indexes; Neurons; Silicon; Training; Continuous Time Linear Equalizer (CTLE); USB; design of experiment (DOE); neural network; response surface methodology (RSM);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electromagnetic Compatibility and Signal Integrity, 2015 IEEE Symposium on
  • Conference_Location
    Santa Clara, CA
  • Print_ISBN
    978-1-4799-1992-5
  • Type

    conf

  • DOI
    10.1109/EMCSI.2015.7107701
  • Filename
    7107701