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Successive matrix squaring algorithm for computing outer inverses
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DOI：10.1016/j.amc.2008.04.037.png)
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Abstract
En 中文
In this paper, we derive a successive matrix squaring (SMS) algorithm to approximate an outer generalized inverse with prescribed range and null space of a given matrix A is an element of C-r(mxn). We generalize the results from the papers [L. Chen, E. V. Krishnamurthy, I. Macleod, Generalized matrix inversion and rank computation by successive matrix powering, Parallel Computing 20 (1994) 297-311; Y. Wei, Successive matrix squaring algorithm for computing Drazin inverse, Appl. Math. Comput. 108 (2000) 67-75; Y. Wei, H. Wu, J. Wei, Successive matrix squaring algorithm for parallel computing the weighted generalized inverse A(MN)(dagger), Appl. Math. Comput. 116 (2000) 289-296], and obtain an algorithm for computing various classes of outer generalized inverses of A. Instead of particular matrices used in these articles, we use an appropriate matrix R is an element of C-s(nxm), S <= r. Numerical examples are presented. (c) 2008 Elsevier Inc. All rights reserved.
Keywords:
generalized inverse
outer inverse
SMS algorithm
full rank factorization
matrix rank
Journal
IF:
3.4
Papers:
2.3W
Citations:
3.3W
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