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Exponential Convergence of a Randomized Kaczmarz Algorithm with Relaxation

  • Yong Cai
  • Yang Zhao
  • Yuchao Tang
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 145)

Abstract

The Kaczmarz method is a well-known iterative algorithm for solving linear system of equations Ax = b. Recently, a randomized version of the algorithm has been introduced. It was proved that for the system Ax = b or Ax ≈ b + r, where r is an arbitrary error vector, the randomized Kaczmarz algorithm converges with expected exponential rate. In the present paper, we study the randomized Kaczmarz algorithm with relaxation and prove that it converges with expected exponential rate for the system of Ax = b and Ax ≈ b + r. The numerical experiments of the randomized Kaczmarz algorithm with relaxation are provided to demonstrate the convergence results.

Keywords

Iteration Number Relaxation Parameter Exponential Rate Exponential Convergence Fourier Anal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Yong Cai
    • 1
  • Yang Zhao
    • 1
  • Yuchao Tang
    • 2
  1. 1.Department of MathematicsNanChang UniversityNanchangP.R. China
  2. 2.Institute for Information and System Science, Faculty of ScienceXi’an Jiaotong UniversityXi’anP.R. China

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