Computation of weighted Moore–Penrose inverse through Gauss–Jordan elimination on bordered matrices

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摘要

In this paper, two new algorithms for computing the Weighted Moore–Penrose inverse AM,N† of a general matrix A for weights M and N which are based on elementary row and column operations on two appropriate block partitioned matrices are introduced and investigated. The computational complexity of the introduced two algorithms is analyzed in detail. These two algorithms proposed in this paper are always faster than those in Sheng and Chen (2013) and Ji (2014), respectively, by comparing their computational complexities. In the end, an example is presented to demonstrate the two new algorithms.

论文关键词:Partitioned matrix,Gauss–Jordan elimination,Weighted Moore–Penrose inverse,Computational complexity

论文评审过程:Received 11 December 2016, Revised 15 June 2017, Accepted 20 November 2017, Available online 24 December 2017, Version of Record 24 December 2017.

论文官网地址:https://doi.org/10.1016/j.amc.2017.11.041