GAUSSIAN ELIMINATION IS NOT OPTIMAL
GAUSSIAN ELIMINATION IS NOT OPTIMAL
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DOI:
10.1007/bf02165411
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发表时间:
1969-01-01
影响因子:
2.1
通讯作者:
STRASSEN, V
中科院分区:
文献类型:
--
作者:
STRASSEN, V
Received December 12, t 968 t. Below we will give an algorithm which computes the coefficients of the product of two square matrices A and B of order n from the coefficients of A and B with tess than 4.7-nlg7 arithmetical operations (all logarithms in this paper are for base 2, thus tog 7~ 2.8; the usual method requires approximately 2n 3 arithmetical operations). The algorithm induces algorithms for inverting a matrix of order n, solving a system of n linear equations in n unknowns, computing a determinant of order n etc. all requiring less than const nlg 7 arithmetical operations.This fact should be compared with the result of KLYUYEV and KOKOVKINSHCHERBAK [1] that Gaussian elimination for solving a system of linearequations is optimal if one restricts oneself to operations upon rows and columns as a whole. We also note that WlNOGRAD [21 modifies the usual algorithms for matrix multiplication and inversion and for solving systems of linear equations, trading roughly half of the multiplications for additions and subtractions. It is a pleasure to thank D. BRILLINGER for inspiring discussions about the present subject and ST. COOK and B. PARLETT for encouraging me to write this paper. 2. We define algorithms e~,~ which multiply matrices of order m2, by induction on k:~, 0 is the usual algorithm, for matrix multiplication (requiring ma multiplications and m 2 (m-t) additions), e~, k already being known, define~,~+ t as follows: