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SUBROUTINE AB13ED( N, A, LDA, LOW, HIGH, TOL, DWORK, LDWORK,
$ INFO )
C
C SLICOT RELEASE 5.0.
C
C Copyright (c) 2002-2009 NICONET e.V.
C
C This program is free software: you can redistribute it and/or
C modify it under the terms of the GNU General Public License as
C published by the Free Software Foundation, either version 2 of
C the License, or (at your option) any later version.
C
C This program is distributed in the hope that it will be useful,
C but WITHOUT ANY WARRANTY; without even the implied warranty of
C MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
C GNU General Public License for more details.
C
C You should have received a copy of the GNU General Public License
C along with this program. If not, see
C <http://www.gnu.org/licenses/>.
C
C PURPOSE
C
C To estimate beta(A), the 2-norm distance from a real matrix A to
C the nearest complex matrix with an eigenvalue on the imaginary
C axis. The estimate is given as
C
C LOW <= beta(A) <= HIGH,
C
C where either
C
C (1 + TOL) * LOW >= HIGH,
C
C or
C
C LOW = 0 and HIGH = delta,
C
C and delta is a small number approximately equal to the square root
C of machine precision times the Frobenius norm (Euclidean norm)
C of A. If A is stable in the sense that all eigenvalues of A lie
C in the open left half complex plane, then beta(A) is the distance
C to the nearest unstable complex matrix, i.e., the complex
C stability radius.
C
C ARGUMENTS
C
C Input/Output Parameters
C
C N (input) INTEGER
C The order of the matrix A. N >= 0.
C
C A (input) DOUBLE PRECISION array, dimension (LDA,N)
C The leading N-by-N part of this array must contain the
C matrix A.
C
C LDA INTEGER
C The leading dimension of array A. LDA >= MAX(1,N).
C
C LOW (output) DOUBLE PRECISION
C A lower bound for beta(A).
C
C HIGH (output) DOUBLE PRECISION
C An upper bound for beta(A).
C
C Tolerances
C
C TOL DOUBLE PRECISION
C Specifies the accuracy with which LOW and HIGH approximate
C beta(A). If the user sets TOL to be less than SQRT(EPS),
C where EPS is the machine precision (see LAPACK Library
C Routine DLAMCH), then the tolerance is taken to be
C SQRT(EPS).
C The recommended value is TOL = 9, which gives an estimate
C of beta(A) correct to within an order of magnitude.
C
C Workspace
C
C DWORK DOUBLE PRECISION array, dimension (LDWORK)
C On exit, if INFO = 0, DWORK(1) returns the optimal value
C of LDWORK.
C
C LDWORK INTEGER
C The length of the array DWORK.
C LDWORK >= MAX( 1, 3*N*(N+1) ).
C For optimum performance LDWORK should be larger.
C
C Error Indicator
C
C INFO INTEGER
C = 0: successful exit;
C < 0: if INFO = -i, the i-th argument had an illegal
C value;
C = 1: the QR algorithm (LAPACK Library routine DHSEQR)
C fails to converge; this error is very rare.
C
C METHOD
C
C Let beta(A) be the 2-norm distance from a real matrix A to the
C nearest complex matrix with an eigenvalue on the imaginary axis.
C It is known that beta(A) = minimum of the smallest singular
C value of (A - jwI), where I is the identity matrix and j**2 = -1,
C and the minimum is taken over all real w.
C The algorithm computes a lower bound LOW and an upper bound HIGH
C for beta(A) by a bisection method in the following way. Given a
C non-negative real number sigma, the Hamiltonian matrix H(sigma)
C is constructed:
C
C | A -sigma*I | | A G |
C H(sigma) = | | := | | .
C | sigma*I -A' | | F -A' |
C
C It can be shown [1] that H(sigma) has an eigenvalue whose real
C part is zero if and only if sigma >= beta. Any lower and upper
C bounds on beta(A) can be improved by choosing a number between
C them and checking to see if H(sigma) has an eigenvalue with zero
C real part. This decision is made by computing the eigenvalues of
C H(sigma) using the square reduced algorithm of Van Loan [2].
C
C REFERENCES
C
C [1] Byers, R.
C A bisection method for measuring the distance of a stable
C matrix to the unstable matrices.
C SIAM J. Sci. Stat. Comput., Vol. 9, No. 5, pp. 875-880, 1988.
C
C [2] Van Loan, C.F.
C A symplectic method for approximating all the eigenvalues of a
C Hamiltonian matrix.
C Linear Algebra and its Applications, Vol 61, 233-251, 1984.
C
C NUMERICAL ASPECTS
C
C Due to rounding errors the computed values of LOW and HIGH can be
C proven to satisfy
C
C LOW - p(n) * sqrt(e) * norm(A) <= beta(A)
C and
C beta(A) <= HIGH + p(n) * sqrt(e) * norm(A),
C
C where p(n) is a modest polynomial of degree 3, e is the machine
C precision and norm(A) is the Frobenius norm of A, see [1].
C The recommended value for TOL is 9 which gives an estimate of
C beta(A) correct to within an order of magnitude.
C AB13ED requires approximately 38*N**3 flops for TOL = 9.
C
C CONTRIBUTOR
C
C R. Byers, the routines BISEC and BISEC0 (January, 1995).
C
C REVISIONS
C
C Release 4.0: V. Sima, Katholieke Univ. Leuven, Belgium, Dec. 1999.
C V. Sima, Research Institute for Informatics, Bucharest, Jan. 2003.
C
C KEYWORDS
C
C Distances, eigenvalue, eigenvalue perturbation, norms, stability
C radius.
C
C ******************************************************************
C
C .. Parameters ..
DOUBLE PRECISION ZERO, ONE
PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0 )
C .. Scalar Arguments ..
DOUBLE PRECISION HIGH, LOW, TOL
INTEGER INFO, LDA, LDWORK, N
C .. Array Arguments ..
DOUBLE PRECISION A(LDA,*), DWORK(*)
C .. Local Scalars ..
INTEGER I, IA2, IAA, IGF, IHI, ILO, IWI, IWK, IWR,
$ JWORK, MINWRK, N2
DOUBLE PRECISION ANRM, SEPS, SFMN, SIGMA, TAU, TEMP, TOL1, TOL2
LOGICAL RNEG, SUFWRK
C .. Local Arrays ..
DOUBLE PRECISION DUMMY(1), DUMMY2(1,1)
C .. External Functions ..
DOUBLE PRECISION DLAMCH, DLANGE
EXTERNAL DLAMCH, DLANGE
C .. External Subroutines ..
EXTERNAL DCOPY, DGEBAL, DGEMM, DHSEQR, DLACPY, DSYMM,
$ DSYMV, MA02ED, MB04ZD, XERBLA
C .. Intrinsic Functions ..
INTRINSIC ABS, DBLE, MAX, SQRT
C .. Executable Statements ..
C
C Test the input scalar arguments.
C
INFO = 0
MINWRK = 3*N*( N + 1 )
C
IF( N.LT.0 ) THEN
INFO = -1
ELSE IF( LDA.LT.MAX( 1, N ) ) THEN
INFO = -3
ELSE IF( LDWORK.LT.MAX( 1, MINWRK ) ) THEN
INFO = -8
END IF
C
IF ( INFO.NE.0 ) THEN
C
C Error return.
C
CALL XERBLA( 'AB13ED', -INFO )
RETURN
END IF
C
C Quick return if possible.
C
LOW = ZERO
IF ( N.EQ.0 ) THEN
HIGH = ZERO
DWORK(1) = ONE
RETURN
END IF
C
C Indices for splitting the work array.
C (Note: Comments in the code beginning "Workspace:" describe the
C minimal amount of real workspace needed at that point in the
C code, as well as the preferred amount for good performance.)
C
N2 = N*N
IGF = 1
IA2 = IGF + N2 + N
IAA = IA2 + N2
IWK = IAA + N2
IWR = IAA
IWI = IWR + N
C
SUFWRK = LDWORK-IWK.GE.N2
C
C Computation of the tolerances and the threshold for termination of
C the bisection method. SEPS is the square root of the machine
C precision.
C
SFMN = DLAMCH( 'Safe minimum' )
SEPS = SQRT( DLAMCH( 'Epsilon' ) )
TAU = ONE + MAX( TOL, SEPS )
ANRM = DLANGE( 'Frobenius', N, N, A, LDA, DWORK )
TOL1 = SEPS * ANRM
TOL2 = TOL1 * DBLE( 2*N )
C
C Initialization of the bisection method.
C
HIGH = ANRM
C
C WHILE ( HIGH > TAU*MAX( TOL1, LOW ) ) DO
10 IF ( HIGH.GT.( TAU*MAX( TOL1, LOW ) ) ) THEN
SIGMA = SQRT( HIGH ) * SQRT( MAX( TOL1, LOW ) )
C
C Set up H(sigma).
C Workspace: N*(N+1)+2*N*N.
C
CALL DLACPY( 'Full', N, N, A, LDA, DWORK(IAA), N )
DWORK(IGF) = SIGMA
DWORK(IGF+N) = -SIGMA
DUMMY(1) = ZERO
CALL DCOPY( N-1, DUMMY, 0, DWORK(IGF+1), 1 )
C
DO 20 I = IGF, IA2 - N - 2, N + 1
CALL DCOPY( N+1, DWORK(I), 1, DWORK(I+N+1), 1 )
20 CONTINUE
C
C Computation of the eigenvalues by the square reduced algorithm.
C Workspace: N*(N+1)+2*N*N+2*N.
C
CALL MB04ZD( 'No vectors', N, DWORK(IAA), N, DWORK(IGF), N,
$ DUMMY2, 1, DWORK(IWK), INFO )
C
C Form the matrix A*A + F*G.
C Workspace: need N*(N+1)+2*N*N+N;
C prefer N*(N+1)+3*N*N.
C
JWORK = IA2
IF ( SUFWRK )
$ JWORK = IWK
C
CALL DLACPY( 'Lower', N, N, DWORK(IGF), N, DWORK(JWORK), N )
CALL MA02ED( 'Lower', N, DWORK(JWORK), N )
C
IF ( SUFWRK ) THEN
C
C Use BLAS 3 calculation.
C
CALL DSYMM( 'Left', 'Upper', N, N, ONE, DWORK(IGF+N), N,
$ DWORK(JWORK), N, ZERO, DWORK(IA2), N )
ELSE
C
C Use BLAS 2 calculation.
C
DO 30 I = 1, N
CALL DSYMV( 'Upper', N, ONE, DWORK(IGF+N), N,
$ DWORK(IA2+N*(I-1)), 1, ZERO, DWORK(IWK), 1 )
CALL DCOPY( N, DWORK(IWK), 1, DWORK(IA2+N*(I-1)), 1 )
30 CONTINUE
C
END IF
C
CALL DGEMM( 'NoTranspose', 'NoTranspose', N, N, N, ONE,
$ DWORK(IAA), N, DWORK(IAA), N, ONE, DWORK(IA2), N )
C
C Find the eigenvalues of A*A + F*G.
C Workspace: N*(N+1)+N*N+3*N.
C
JWORK = IWI + N
CALL DGEBAL( 'Scale', N, DWORK(IA2), N, ILO, IHI, DWORK(JWORK),
$ I )
CALL DHSEQR( 'Eigenvalues', 'NoSchurVectors', N, ILO, IHI,
$ DWORK(IA2), N, DWORK(IWR), DWORK(IWI), DUMMY2, 1,
$ DWORK(JWORK), N, INFO )
C
IF ( INFO.NE.0 ) THEN
INFO = 1
RETURN
END IF
C
C (DWORK(IWR+i), DWORK(IWI+i)), i = 0,...,N-1, contain the
C squares of the eigenvalues of H(sigma).
C
I = 0
RNEG = .FALSE.
C WHILE ( ( DWORK(IWR+i),DWORK(IWI+i) ) not real positive
C .AND. I < N ) DO
40 IF ( .NOT.RNEG .AND. I.LT.N ) THEN
TEMP = ABS( DWORK(IWI+I) )
IF ( TOL1.GT.SFMN ) TEMP = TEMP / TOL1
RNEG = ( ( DWORK(IWR+I).LT.ZERO ) .AND. ( TEMP.LE.TOL2 ) )
I = I + 1
GO TO 40
C END WHILE 40
END IF
IF ( RNEG ) THEN
HIGH = SIGMA
ELSE
LOW = SIGMA
END IF
GO TO 10
C END WHILE 10
END IF
C
C Set optimal workspace dimension.
C
DWORK(1) = DBLE( MAX( 4*N2 + N, MINWRK ) )
C
C *** Last line of AB13ED ***
END
|
