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<HEAD><TITLE>SB03OS - SLICOT Library Routine Documentation</TITLE>
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<H2><A Name="SB03OS">SB03OS</A></H2>
<H3>
Solving (for Cholesky factor) stable continuous- or discrete-time complex Lyapunov equations, with matrices S and R triangular
</H3>
<A HREF ="#Specification"><B>[Specification]</B></A>
<A HREF ="#Arguments"><B>[Arguments]</B></A>
<A HREF ="#Method"><B>[Method]</B></A>
<A HREF ="#References"><B>[References]</B></A>
<A HREF ="#Comments"><B>[Comments]</B></A>
<A HREF ="#Example"><B>[Example]</B></A>
<P>
<B><FONT SIZE="+1">Purpose</FONT></B>
<PRE> H
To solve for X = op(U) *op(U) either the stable non-negative
definite continuous-time Lyapunov equation
H 2 H
op(S) *X + X*op(S) = -scale *op(R) *op(R), (1)
or the convergent non-negative definite discrete-time Lyapunov
equation
H 2 H
op(S) *X*op(S) - X = -scale *op(R) *op(R), (2)
where op(K) = K or K**H (i.e., the conjugate transpose of the
matrix K), S and R are complex N-by-N upper triangular matrices,
and scale is an output scale factor, set less than or equal to 1
to avoid overflow in X. The diagonal elements of the matrix R must
be real non-negative.
In the case of equation (1) the matrix S must be stable (that is,
all the eigenvalues of S must have negative real parts), and for
equation (2) the matrix S must be convergent (that is, all the
eigenvalues of S must lie inside the unit circle).
</PRE>
<A name="Specification"><B><FONT SIZE="+1">Specification</FONT></B></A>
<PRE>
SUBROUTINE SB03OS( DISCR, LTRANS, N, S, LDS, R, LDR, SCALE, DWORK,
$ ZWORK, INFO )
C .. Scalar Arguments ..
DOUBLE PRECISION SCALE
INTEGER INFO, LDR, LDS, N
LOGICAL DISCR, LTRANS
C .. Array Arguments ..
COMPLEX*16 R(LDR,*), S(LDS,*), ZWORK(*)
DOUBLE PRECISION DWORK(*)
</PRE>
<A name="Arguments"><B><FONT SIZE="+1">Arguments</FONT></B></A>
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<B>Mode Parameters</B>
<PRE>
DISCR LOGICAL
Specifies the type of Lyapunov equation to be solved as
follows:
= .TRUE. : Equation (2), discrete-time case;
= .FALSE.: Equation (1), continuous-time case.
LTRANS LOGICAL
Specifies the form of op(K) to be used, as follows:
= .FALSE.: op(K) = K (No transpose);
= .TRUE. : op(K) = K**H (Conjugate transpose).
</PRE>
<B>Input/Output Parameters</B>
<PRE>
N (input) INTEGER
The order of the matrices S and R. N >= 0.
S (input) COMPLEX*16 array of dimension (LDS,N)
The leading N-by-N upper triangular part of this array
must contain the upper triangular matrix.
The elements below the upper triangular part of the array
S are not referenced.
LDS INTEGER
The leading dimension of array S. LDS >= MAX(1,N).
R (input/output) COMPLEX*16 array of dimension (LDR,N)
On entry, the leading N-by-N upper triangular part of this
array must contain the upper triangular matrix R, with
real non-negative entries on its main diagonal.
On exit, the leading N-by-N upper triangular part of this
array contains the upper triangular matrix U, with real
non-negative entries on its main diagonal.
The strictly lower triangle of R is not referenced.
LDR INTEGER
The leading dimension of array R. LDR >= MAX(1,N).
SCALE (output) DOUBLE PRECISION
The scale factor, scale, set less than or equal to 1 to
prevent the solution overflowing.
</PRE>
<B>Workspace</B>
<PRE>
DWORK DOUBLE PRECISION array, dimension (N-1)
ZWORK COMPLEX*16 array, dimension (2*N-2)
</PRE>
<B>Error Indicator</B>
<PRE>
INFO INTEGER
= 0: successful exit;
< 0: if INFO = -i, the i-th argument had an illegal
value;
= 3: if the matrix S is not stable (that is, one or more
of the eigenvalues of S has a non-negative real
part), if DISCR = .FALSE., or not convergent (that
is, one or more of the eigenvalues of S lies outside
the unit circle), if DISCR = .TRUE..
</PRE>
<A name="Method"><B><FONT SIZE="+1">Method</FONT></B></A>
<PRE>
The method used by the routine is based on a variant of the
Bartels and Stewart backward substitution method [1], that finds
the Cholesky factor op(U) directly without first finding X and
without the need to form the normal matrix op(R)'*op(R) [2].
The continuous-time Lyapunov equation in the canonical form
H H H 2 H
op(S) *op(U) *op(U) + op(U) *op(U)*op(S) = -scale *op(R) *op(R),
or the discrete-time Lyapunov equation in the canonical form
H H H 2 H
op(S) *op(U) *op(U)*op(S) - op(U) *op(U) = -scale *op(R) *op(R),
where U and R are upper triangular, is solved for U.
</PRE>
<A name="References"><B><FONT SIZE="+1">References</FONT></B></A>
<PRE>
[1] Bartels, R.H. and Stewart, G.W.
Solution of the matrix equation A'X + XB = C.
Comm. A.C.M., 15, pp. 820-826, 1972.
[2] Hammarling, S.J.
Numerical solution of the stable, non-negative definite
Lyapunov equation.
IMA J. Num. Anal., 2, pp. 303-325, 1982.
</PRE>
<A name="Numerical Aspects"><B><FONT SIZE="+1">Numerical Aspects</FONT></B></A>
<PRE> 3
The algorithm requires 0(N ) operations and is backward stable.
</PRE>
<A name="Comments"><B><FONT SIZE="+1">Further Comments</FONT></B></A>
<PRE>
The Lyapunov equation may be very ill-conditioned. In particular
if S is only just stable (or convergent) then the Lyapunov
equation will be ill-conditioned. "Large" elements in U relative
to those of S and R, or a "small" value for scale, is a symptom
of ill-conditioning. A condition estimate can be computed using
SLICOT Library routine SB03MD.
</PRE>
<A name="Example"><B><FONT SIZE="+1">Example</FONT></B></A>
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<B>Program Text</B>
<PRE>
None
</PRE>
<B>Program Data</B>
<PRE>
None
</PRE>
<B>Program Results</B>
<PRE>
None
</PRE>
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