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slaic1(l) [redhat man page]

SLAIC1(l)								 )								 SLAIC1(l)

NAME
SLAIC1 - applie one step of incremental condition estimation in its simplest version SYNOPSIS
SUBROUTINE SLAIC1( JOB, J, X, SEST, W, GAMMA, SESTPR, S, C ) INTEGER J, JOB REAL C, GAMMA, S, SEST, SESTPR REAL W( J ), X( J ) PURPOSE
SLAIC1 applies one step of incremental condition estimation in its simplest version: Let x, twonorm(x) = 1, be an approximate singular vec- tor of an j-by-j lower triangular matrix L, such that twonorm(L*x) = sest Then SLAIC1 computes sestpr, s, c such that the vector [ s*x ] xhat = [ c ] is an approximate singular vector of [ L 0 ] Lhat = [ w' gamma ] in the sense that twonorm(Lhat*xhat) = sestpr. Depending on JOB, an estimate for the largest or smallest singular value is computed. Note that [s c]' and sestpr**2 is an eigenpair of the system diag(sest*sest, 0) + [alpha gamma] * [ alpha ] [ gamma ] where alpha = x'*w. ARGUMENTS
JOB (input) INTEGER = 1: an estimate for the largest singular value is computed. = 2: an estimate for the smallest singular value is computed. J (input) INTEGER Length of X and W X (input) REAL array, dimension (J) The j-vector x. SEST (input) REAL Estimated singular value of j by j matrix L W (input) REAL array, dimension (J) The j-vector w. GAMMA (input) REAL The diagonal element gamma. SESTPR (output) REAL Estimated singular value of (j+1) by (j+1) matrix Lhat. S (output) REAL Sine needed in forming xhat. C (output) REAL Cosine needed in forming xhat. LAPACK version 3.0 15 June 2000 SLAIC1(l)

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slaic1.f(3)							      LAPACK							       slaic1.f(3)

NAME
slaic1.f - SYNOPSIS
Functions/Subroutines subroutine slaic1 (JOB, J, X, SEST, W, GAMMA, SESTPR, S, C) SLAIC1 applies one step of incremental condition estimation. Function/Subroutine Documentation subroutine slaic1 (integerJOB, integerJ, real, dimension( j )X, realSEST, real, dimension( j )W, realGAMMA, realSESTPR, realS, realC) SLAIC1 applies one step of incremental condition estimation. Purpose: SLAIC1 applies one step of incremental condition estimation in its simplest version: Let x, twonorm(x) = 1, be an approximate singular vector of an j-by-j lower triangular matrix L, such that twonorm(L*x) = sest Then SLAIC1 computes sestpr, s, c such that the vector [ s*x ] xhat = [ c ] is an approximate singular vector of [ L 0 ] Lhat = [ w**T gamma ] in the sense that twonorm(Lhat*xhat) = sestpr. Depending on JOB, an estimate for the largest or smallest singular value is computed. Note that [s c]**T and sestpr**2 is an eigenpair of the system diag(sest*sest, 0) + [alpha gamma] * [ alpha ] [ gamma ] where alpha = x**T*w. Parameters: JOB JOB is INTEGER = 1: an estimate for the largest singular value is computed. = 2: an estimate for the smallest singular value is computed. J J is INTEGER Length of X and W X X is REAL array, dimension (J) The j-vector x. SEST SEST is REAL Estimated singular value of j by j matrix L W W is REAL array, dimension (J) The j-vector w. GAMMA GAMMA is REAL The diagonal element gamma. SESTPR SESTPR is REAL Estimated singular value of (j+1) by (j+1) matrix Lhat. S S is REAL Sine needed in forming xhat. C C is REAL Cosine needed in forming xhat. Author: Univ. of Tennessee Univ. of California Berkeley Univ. of Colorado Denver NAG Ltd. Date: September 2012 Definition at line 135 of file slaic1.f. Author Generated automatically by Doxygen for LAPACK from the source code. Version 3.4.2 Tue Sep 25 2012 slaic1.f(3)
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