• DocumentCode
    75328
  • Title

    A Computationally Efficient Nonlinear Least Squares Method Using Random Basis Functions

  • Author

    Kay, Steven

  • Author_Institution
    Dept. of Electr., Comput., & Biomed. Eng., Univ. of Rhode Island, Kingston, RI, USA
  • Volume
    20
  • Issue
    7
  • fYear
    2013
  • fDate
    Jul-13
  • Firstpage
    721
  • Lastpage
    724
  • Abstract
    A method to obtain parameter estimates in a nonlinear least squares problem is proposed. Its main advantage is computational efficiency and can be used when a direct grid search cannot. The approach is based on the theory of random basis functions. An example of its application to frequency estimation is given and other applications discussed.
  • Keywords
    frequency estimation; least mean squares methods; random functions; signal representation; frequency estimation; nonlinear least square method; parameter estimation; random basis function; signal representation; Bandwidth; Frequency estimation; Least squares approximations; Maximum likelihood estimation; Quantization (signal); Vectors; Estimation; signal representations; signal resolution;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2013.2264808
  • Filename
    6519322