• DocumentCode
    1609934
  • Title

    Recursive EM and SAGE algorithms

  • Author

    Chung, Pei Jung ; Böhme, Johann F.

  • Author_Institution
    Dept. of Electr. Eng. & Inf. Sci., Ruhr-Univ., Bochum, Germany
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    540
  • Lastpage
    543
  • Abstract
    This work is concerned with recursive procedures in which the data run through sequentially. Two stochastic approximation recursions derived from the EM (expectation-maximization).and SAGE (space-alternating generalized expectation-maximization). algorithms are proposed. We show that under regularity conditions, these recursions lead to strong consistency and asymptotic normality. Although the recursive EM and SAGE algorithm do not have the optimal convergence rate, they are usually easy to implement. As an example, we derive recursive procedures for direction of arrival (DOA) estimation. In numerical experiments both algorithms provide good results for low computational cost
  • Keywords
    approximation theory; convergence of numerical methods; direction-of-arrival estimation; iterative methods; recursive estimation; stochastic processes; DOA estimation; asymptotic normality; computational cost; consistency; convergence; direction of arrival estimation; recursive EM algorithms; recursive SAGE algorithms; regularity conditions; space-alternating generalized expectation-maximization algorithm; stochastic approximation recursions; Approximation algorithms; Computational efficiency; Convergence; Direction of arrival estimation; Information science; Iterative algorithms; Parameter estimation; Recursive estimation; Stability; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on
  • Print_ISBN
    0-7803-7011-2
  • Type

    conf

  • DOI
    10.1109/SSP.2001.955342
  • Filename
    955342