• DocumentCode
    1528200
  • Title

    Equivalence between voltage-processing methods and discrete orthogonal Legendre polynomial (DOLP) approach

  • Author

    Brookner, Eli

  • Author_Institution
    Raytheon Co., Sudbury, MA, USA
  • Volume
    47
  • Issue
    8
  • fYear
    1999
  • fDate
    8/1/1999 12:00:00 AM
  • Firstpage
    2273
  • Lastpage
    2278
  • Abstract
    There are three methods for solving the least-squares estimation (LSE) problem. (1) the power method; (2) the voltage-processing method (square-root method); and (3) the discrete orthogonal Legendre polynomial (DOLP) method. The first involves a matrix inversion and is sensitive to computer round-off errors. The second and third do not require a matrix inversion and are not as sensitive to computer round-off errors. It is shown that the voltage-processing LSE methods (Givens, Householder, and Gram-Schmidt) become the discrete orthogonal Legendre polynomial (DOLP) LSE method when the data can be modeled by a polynomial function and the times between measurements are equal. Furthermore, when the data can be modeled by a polynomial function and the time between measurements are equal, the DOLP is the preferred method because it does not require an orthonormal transformation and it does not require the back-substitution method
  • Keywords
    least mean squares methods; matrix inversion; measurement; polynomials; signal processing; DOLP approach; LSE problem solution; computer round-off errors; discrete orthogonal Legendre polynomial; least-squares estimation; matrix inversion; measurements time; polynomial function; power method; square-root method; voltage-processing LSE methods; voltage-processing method; voltage-processing methods; Additive noise; Least squares approximation; Noise measurement; Polynomials; Roundoff errors; Time measurement; Voltage;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.774770
  • Filename
    774770