slacn2 (3)  Linux Manuals
NAME
slacn2.f 
SYNOPSIS
Functions/Subroutines
subroutine slacn2 (N, V, X, ISGN, EST, KASE, ISAVE)
SLACN2 estimates the 1norm of a square matrix, using reverse communication for evaluating matrixvector products.
Function/Subroutine Documentation
subroutine slacn2 (integerN, real, dimension( * )V, real, dimension( * )X, integer, dimension( * )ISGN, realEST, integerKASE, integer, dimension( 3 )ISAVE)
SLACN2 estimates the 1norm of a square matrix, using reverse communication for evaluating matrixvector products.
Purpose:

SLACN2 estimates the 1norm of a square, real matrix A. Reverse communication is used for evaluating matrixvector products.
Parameters:

N
N is INTEGER The order of the matrix. N >= 1.
VV is REAL array, dimension (N) On the final return, V = A*W, where EST = norm(V)/norm(W) (W is not returned).
XX is REAL array, dimension (N) On an intermediate return, X should be overwritten by A * X, if KASE=1, A**T * X, if KASE=2, and SLACN2 must be recalled with all the other parameters unchanged.
ISGNISGN is INTEGER array, dimension (N)
ESTEST is REAL On entry with KASE = 1 or 2 and ISAVE(1) = 3, EST should be unchanged from the previous call to SLACN2. On exit, EST is an estimate (a lower bound) for norm(A).
KASEKASE is INTEGER On the initial call to SLACN2, KASE should be 0. On an intermediate return, KASE will be 1 or 2, indicating whether X should be overwritten by A * X or A**T * X. On the final return from SLACN2, KASE will again be 0.
ISAVEISAVE is INTEGER array, dimension (3) ISAVE is used to save variables between calls to SLACN2
Author:

Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.
Date:
 September 2012
Further Details:

Originally named SONEST, dated March 16, 1988. This is a thread safe version of SLACON, which uses the array ISAVE in place of a SAVE statement, as follows: SLACON SLACN2 JUMP ISAVE(1) J ISAVE(2) ITER ISAVE(3)
Contributors:
 Nick Higham, University of Manchester
References:

N.J. Higham, 'FORTRAN codes for estimating the onenorm of
a real or complex matrix, with applications to condition estimation', ACM Trans. Math. Soft., vol. 14, no. 4, pp. 381396, December 1988.
Definition at line 137 of file slacn2.f.
Author
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