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AIMS Mathematics

2020, Volume 5, Issue 3: 1680-1692. doi: 10.3934/math.2020113
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Research article

An efficient hyperpower iterative method for computing weighted MoorePenrose inverse

  • School of Mathematics, Thapar Institute of Engineering and Technology, Patiala 147004, India
  • Received: 06 October 2019 Accepted: 10 February 2020 Published: 13 February 2020

  • MSC : 15A09, 65F30

  • In this paper, we propose a new hyperpower iterative method for approximating the weighted Moore-Penrose inverse of a given matrix. The main objective of the current work is to minimize the computational complexity of the hyperpower iterative method using some transformations. The proposed method attains the fifth-order of convergence using four matrix multiplications per iteration step. The theoretical convergence analysis of the method is discussed in detail. A wide range of numerical problems is considered from scientific literature, which demonstrates the applicability and superiority of the proposed method.

    Citation: Manpreet Kaur, Munish Kansal, Sanjeev Kumar. An efficient hyperpower iterative method for computing weighted MoorePenrose inverse[J]. AIMS Mathematics, 2020, 5(3): 1680-1692. doi: 10.3934/math.2020113

    Related Papers:

  • In this paper, we propose a new hyperpower iterative method for approximating the weighted Moore-Penrose inverse of a given matrix. The main objective of the current work is to minimize the computational complexity of the hyperpower iterative method using some transformations. The proposed method attains the fifth-order of convergence using four matrix multiplications per iteration step. The theoretical convergence analysis of the method is discussed in detail. A wide range of numerical problems is considered from scientific literature, which demonstrates the applicability and superiority of the proposed method.


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