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SUBROUTINE IB03AD( INIT, ALG, STOR, NOBR, M, L, NSMP, N, NN,
$ ITMAX1, ITMAX2, NPRINT, U, LDU, Y, LDY, X, LX,
$ TOL1, TOL2, IWORK, DWORK, LDWORK, IWARN, INFO )
C
C PURPOSE
C
C To compute a set of parameters for approximating a Wiener system
C in a least-squares sense, using a neural network approach and a
C Levenberg-Marquardt algorithm. Conjugate gradients (CG) or
C Cholesky algorithms are used to solve linear systems of equations.
C The Wiener system is represented as
C
C x(t+1) = A*x(t) + B*u(t)
C z(t) = C*x(t) + D*u(t),
C
C y(t) = f(z(t),wb(1:L)),
C
C where t = 1, 2, ..., NSMP, and f is a nonlinear function,
C evaluated by the SLICOT Library routine NF01AY. The parameter
C vector X is partitioned as X = ( wb(1), ..., wb(L), theta ),
C where wb(i), i = 1 : L, correspond to the nonlinear part, and
C theta corresponds to the linear part. See SLICOT Library routine
C NF01AD for further details.
C
C The sum of squares of the error functions, defined by
C
C e(t) = y(t) - Y(t), t = 1, 2, ..., NSMP,
C
C is minimized, where Y(t) is the measured output vector. The
C functions and their Jacobian matrices are evaluated by SLICOT
C Library routine NF01BB (the FCN routine in the call of MD03AD).
C
C ARGUMENTS
C
C Mode Parameters
C
C INIT CHARACTER*1
C Specifies which parts have to be initialized, as follows:
C = 'L' : initialize the linear part only, X already
C contains an initial approximation of the
C nonlinearity;
C = 'S' : initialize the static nonlinearity only, X
C already contains an initial approximation of the
C linear part;
C = 'B' : initialize both linear and nonlinear parts;
C = 'N' : do not initialize anything, X already contains
C an initial approximation.
C If INIT = 'S' or 'B', the error functions for the
C nonlinear part, and their Jacobian matrices, are evaluated
C by SLICOT Library routine NF01BA (used as a second FCN
C routine in the MD03AD call for the initialization step,
C see METHOD).
C
C ALG CHARACTER*1
C Specifies the algorithm used for solving the linear
C systems involving a Jacobian matrix J, as follows:
C = 'D' : a direct algorithm, which computes the Cholesky
C factor of the matrix J'*J + par*I is used, where
C par is the Levenberg factor;
C = 'I' : an iterative Conjugate Gradients algorithm, which
C only needs the matrix J, is used.
C In both cases, matrix J is stored in a compressed form.
C
C STOR CHARACTER*1
C If ALG = 'D', specifies the storage scheme for the
C symmetric matrix J'*J, as follows:
C = 'F' : full storage is used;
C = 'P' : packed storage is used.
C The option STOR = 'F' usually ensures a faster execution.
C This parameter is not relevant if ALG = 'I'.
C
C Input/Output Parameters
C
C NOBR (input) INTEGER
C If INIT = 'L' or 'B', NOBR is the number of block rows, s,
C in the input and output block Hankel matrices to be
C processed for estimating the linear part. NOBR > 0.
C (In the MOESP theory, NOBR should be larger than n,
C the estimated dimension of state vector.)
C This parameter is ignored if INIT is 'S' or 'N'.
C
C M (input) INTEGER
C The number of system inputs. M >= 0.
C
C L (input) INTEGER
C The number of system outputs. L >= 0, and L > 0, if
C INIT = 'L' or 'B'.
C
C NSMP (input) INTEGER
C The number of input and output samples, t. NSMP >= 0, and
C NSMP >= 2*(M+L+1)*NOBR - 1, if INIT = 'L' or 'B'.
C
C N (input/output) INTEGER
C The order of the linear part.
C If INIT = 'L' or 'B', and N < 0 on entry, the order is
C assumed unknown and it will be found by the routine.
C Otherwise, the input value will be used. If INIT = 'S'
C or 'N', N must be non-negative. The values N >= NOBR,
C or N = 0, are not acceptable if INIT = 'L' or 'B'.
C
C NN (input) INTEGER
C The number of neurons which shall be used to approximate
C the nonlinear part. NN >= 0.
C
C ITMAX1 (input) INTEGER
C The maximum number of iterations for the initialization of
C the static nonlinearity.
C This parameter is ignored if INIT is 'N' or 'L'.
C Otherwise, ITMAX1 >= 0.
C
C ITMAX2 (input) INTEGER
C The maximum number of iterations. ITMAX2 >= 0.
C
C NPRINT (input) INTEGER
C This parameter enables controlled printing of iterates if
C it is positive. In this case, FCN is called with IFLAG = 0
C at the beginning of the first iteration and every NPRINT
C iterations thereafter and immediately prior to return,
C and the current error norm is printed. Other intermediate
C results could be printed by modifying the corresponding
C FCN routine (NF01BA and/or NF01BB). If NPRINT <= 0, no
C special calls of FCN with IFLAG = 0 are made.
C
C U (input) DOUBLE PRECISION array, dimension (LDU, M)
C The leading NSMP-by-M part of this array must contain the
C set of input samples,
C U = ( U(1,1),...,U(1,M); ...; U(NSMP,1),...,U(NSMP,M) ).
C
C LDU INTEGER
C The leading dimension of array U. LDU >= MAX(1,NSMP).
C
C Y (input) DOUBLE PRECISION array, dimension (LDY, L)
C The leading NSMP-by-L part of this array must contain the
C set of output samples,
C Y = ( Y(1,1),...,Y(1,L); ...; Y(NSMP,1),...,Y(NSMP,L) ).
C
C LDY INTEGER
C The leading dimension of array Y. LDY >= MAX(1,NSMP).
C
C X (input/output) DOUBLE PRECISION array dimension (LX)
C On entry, if INIT = 'L', the leading (NN*(L+2) + 1)*L part
C of this array must contain the initial parameters for
C the nonlinear part of the system.
C On entry, if INIT = 'S', the elements lin1 : lin2 of this
C array must contain the initial parameters for the linear
C part of the system, corresponding to the output normal
C form, computed by SLICOT Library routine TB01VD, where
C lin1 = (NN*(L+2) + 1)*L + 1;
C lin2 = (NN*(L+2) + 1)*L + N*(L+M+1) + L*M.
C On entry, if INIT = 'N', the elements 1 : lin2 of this
C array must contain the initial parameters for the
C nonlinear part followed by the initial parameters for the
C linear part of the system, as specified above.
C This array need not be set on entry if INIT = 'B'.
C On exit, the elements 1 : lin2 of this array contain the
C optimal parameters for the nonlinear part followed by the
C optimal parameters for the linear part of the system, as
C specified above.
C
C LX (input/output) INTEGER
C On entry, this parameter must contain the intended length
C of X. If N >= 0, then LX >= NX := lin2 (see parameter X).
C If N is unknown (N < 0 on entry), a large enough estimate
C of N should be used in the formula of lin2.
C On exit, if N < 0 on entry, but LX is not large enough,
C then this parameter contains the actual length of X,
C corresponding to the computed N. Otherwise, its value
C is unchanged.
C
C Tolerances
C
C TOL1 DOUBLE PRECISION
C If INIT = 'S' or 'B' and TOL1 >= 0, TOL1 is the tolerance
C which measures the relative error desired in the sum of
C squares, for the initialization step of nonlinear part.
C Termination occurs when the actual relative reduction in
C the sum of squares is at most TOL1. In addition, if
C ALG = 'I', TOL1 also measures the relative residual of
C the solutions computed by the CG algorithm (for the
C initialization step). Termination of a CG process occurs
C when the relative residual is at most TOL1.
C If the user sets TOL1 < 0, then SQRT(EPS) is used
C instead TOL1, where EPS is the machine precision
C (see LAPACK Library routine DLAMCH).
C This parameter is ignored if INIT is 'N' or 'L'.
C
C TOL2 DOUBLE PRECISION
C If TOL2 >= 0, TOL2 is the tolerance which measures the
C relative error desired in the sum of squares, for the
C whole optimization process. Termination occurs when the
C actual relative reduction in the sum of squares is at
C most TOL2.
C If ALG = 'I', TOL2 also measures the relative residual of
C the solutions computed by the CG algorithm (for the whole
C optimization). Termination of a CG process occurs when the
C relative residual is at most TOL2.
C If the user sets TOL2 < 0, then SQRT(EPS) is used
C instead TOL2. This default value could require many
C iterations, especially if TOL1 is larger. If INIT = 'S'
C or 'B', it is advisable that TOL2 be larger than TOL1,
C and spend more time with cheaper iterations.
C
C Workspace
C
C IWORK INTEGER array, dimension (MAX( 3, LIW1, LIW2 )), where
C LIW1 = LIW2 = 0, if INIT = 'S' or 'N'; otherwise,
C LIW1 = M+L;
C LIW2 = MAX(M*NOBR+N,M*(N+L)).
C On output, if INFO = 0, IWORK(1) and IWORK(2) return the
C (total) number of function and Jacobian evaluations,
C respectively (including the initialization step, if it was
C performed), and if INIT = 'L' or INIT = 'B', IWORK(3)
C specifies how many locations of DWORK contain reciprocal
C condition number estimates (see below); otherwise,
C IWORK(3) = 0.
C
C DWORK DOUBLE PRECISION array, dimension (LDWORK)
C On entry, if desired, and if INIT = 'S' or 'B', the
C entries DWORK(1:4) are set to initialize the random
C numbers generator for the nonlinear part parameters (see
C the description of the argument XINIT of SLICOT Library
C routine MD03AD); this enables to obtain reproducible
C results. The same seed is used for all outputs.
C On exit, if INFO = 0, DWORK(1) returns the optimal value
C of LDWORK, DWORK(2) returns the residual error norm (the
C sum of squares), DWORK(3) returns the number of iterations
C performed, DWORK(4) returns the number of conjugate
C gradients iterations performed, and DWORK(5) returns the
C final Levenberg factor, for optimizing the parameters of
C both the linear part and the static nonlinearity part.
C If INIT = 'S' or INIT = 'B' and INFO = 0, then the
C elements DWORK(6) to DWORK(10) contain the corresponding
C five values for the initialization step (see METHOD).
C (If L > 1, DWORK(10) contains the maximum of the Levenberg
C factors for all outputs.) If INIT = 'L' or INIT = 'B', and
C INFO = 0, DWORK(11) to DWORK(10+IWORK(3)) contain
C reciprocal condition number estimates set by SLICOT
C Library routines IB01AD, IB01BD, and IB01CD.
C On exit, if INFO = -23, DWORK(1) returns the minimum
C value of LDWORK.
C
C LDWORK INTEGER
C The length of the array DWORK.
C In the formulas below, N should be taken not larger than
C NOBR - 1, if N < 0 on entry.
C LDWORK = MAX( LW1, LW2, LW3, LW4 ), where
C LW1 = 0, if INIT = 'S' or 'N'; otherwise,
C LW1 = MAX( 2*(M+L)*NOBR*(2*(M+L)*(NOBR+1)+3) + L*NOBR,
C 4*(M+L)*NOBR*(M+L)*NOBR + (N+L)*(N+M) +
C MAX( LDW1, LDW2 ),
C (N+L)*(N+M) + N + N*N + 2 + N*(N+M+L) +
C MAX( 5*N, 2, MIN( LDW3, LDW4 ), LDW5, LDW6 ),
C where,
C LDW1 >= MAX( 2*(L*NOBR-L)*N+2*N, (L*NOBR-L)*N+N*N+7*N,
C L*NOBR*N +
C MAX( (L*NOBR-L)*N+2*N + (2*M+L)*NOBR+L,
C 2*(L*NOBR-L)*N+N*N+8*N,
C N+4*(M*NOBR+N)+1, M*NOBR+3*N+L ) )
C LDW2 >= 0, if M = 0;
C LDW2 >= L*NOBR*N + M*NOBR*(N+L)*(M*(N+L)+1) +
C MAX( (N+L)**2, 4*M*(N+L)+1 ), if M > 0;
C LDW3 = NSMP*L*(N+1) + 2*N + MAX( 2*N*N, 4*N ),
C LDW4 = N*(N+1) + 2*N +
C MAX( N*L*(N+1) + 2*N*N + L*N, 4*N );
C LDW5 = NSMP*L + (N+L)*(N+M) + 3*N+M+L;
C LDW6 = NSMP*L + (N+L)*(N+M) + N +
C MAX(1, N*N*L + N*L + N, N*N +
C MAX(N*N + N*MAX(N,L) + 6*N + MIN(N,L),
C N*M));
C LW2 = LW3 = 0, if INIT = 'L' or 'N'; otherwise,
C LW2 = NSMP*L +
C MAX( 5, NSMP + 2*BSN + NSMP*BSN +
C MAX( 2*NN + BSN, LDW7 ) );
C LDW7 = BSN*BSN, if ALG = 'D' and STOR = 'F';
C LDW7 = BSN*(BSN+1)/2, if ALG = 'D' and STOR = 'P';
C LDW7 = 3*BSN + NSMP, if ALG = 'I';
C LW3 = MAX( LDW8, NSMP*L + (N+L)*(2*N+M) + 2*N );
C LDW8 = NSMP*L + (N+L)*(N+M) + 3*N+M+L, if M > 0;
C LDW8 = NSMP*L + (N+L)*N + 2*N+L, if M = 0;
C LW4 = MAX( 5, NSMP*L + 2*NX + NSMP*L*( BSN + LTHS ) +
C MAX( L1 + NX, NSMP*L + L1, L2 ) ),
C L0 = MAX( N*(N+L), N+M+L ), if M > 0;
C L0 = MAX( N*(N+L), L ), if M = 0;
C L1 = NSMP*L + MAX( 2*NN, (N+L)*(N+M) + 2*N + L0);
C L2 = NX*NX, if ALG = 'D' and STOR = 'F';
C L2 = NX*(NX+1)/2, if ALG = 'D' and STOR = 'P';
C L2 = 3*NX + NSMP*L, if ALG = 'I',
C with BSN = NN*( L + 2 ) + 1,
C LTHS = N*( L + M + 1 ) + L*M.
C For optimum performance LDWORK should be larger.
C
C Warning Indicator
C
C IWARN INTEGER
C = 0: no warning;
C < 0: the user set IFLAG = IWARN in (one of) the
C subroutine(s) FCN, i.e., NF01BA, if INIT = 'S'
C or 'B', and/or NF01BB; this value cannot be returned
C without changing the FCN routine(s);
C otherwise, IWARN has the value k*100 + j*10 + i,
C where k is defined below, i refers to the whole
C optimization process, and j refers to the
C initialization step (j = 0, if INIT = 'L' or 'N'),
C and the possible values for i and j have the
C following meaning (where TOL* denotes TOL1 or TOL2,
C and similarly for ITMAX*):
C = 1: the number of iterations has reached ITMAX* without
C satisfying the convergence condition;
C = 2: if alg = 'I' and in an iteration of the Levenberg-
C Marquardt algorithm, the CG algorithm finished
C after 3*NX iterations (or 3*(lin1-1) iterations, for
C the initialization phase), without achieving the
C precision required in the call;
C = 3: the cosine of the angle between the vector of error
C function values and any column of the Jacobian is at
C most FACTOR*EPS in absolute value (FACTOR = 100);
C = 4: TOL* is too small: no further reduction in the sum
C of squares is possible.
C The digit k is normally 0, but if INIT = 'L' or 'B', it
C can have a value in the range 1 to 6 (see IB01AD, IB01BD
C and IB01CD). In all these cases, the entries DWORK(1:5),
C DWORK(6:10) (if INIT = 'S' or 'B'), and
C DWORK(11:10+IWORK(3)) (if INIT = 'L' or 'B'), are set as
C described above.
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 otherwise, INFO has the value k*100 + j*10 + i,
C where k is defined below, i refers to the whole
C optimization process, and j refers to the
C initialization step (j = 0, if INIT = 'L' or 'N'),
C and the possible values for i and j have the
C following meaning:
C = 1: the routine FCN returned with INFO <> 0 for
C IFLAG = 1;
C = 2: the routine FCN returned with INFO <> 0 for
C IFLAG = 2;
C = 3: ALG = 'D' and SLICOT Library routines MB02XD or
C NF01BU (or NF01BV, if INIT = 'S' or 'B') or
C ALG = 'I' and SLICOT Library routines MB02WD or
C NF01BW (or NF01BX, if INIT = 'S' or 'B') returned
C with INFO <> 0.
C In addition, if INIT = 'L' or 'B', i could also be
C = 4: if a Lyapunov equation could not be solved;
C = 5: if the identified linear system is unstable;
C = 6: if the QR algorithm failed on the state matrix
C of the identified linear system.
C The digit k is normally 0, but if INIT = 'L' or 'B', it
C can have a value in the range 1 to 10 (see IB01AD/IB01BD).
C
C METHOD
C
C If INIT = 'L' or 'B', the linear part of the system is
C approximated using the combined MOESP and N4SID algorithm. If
C necessary, this algorithm can also choose the order, but it is
C advantageous if the order is already known.
C
C If INIT = 'S' or 'B', the output of the approximated linear part
C is computed and used to calculate an approximation of the static
C nonlinearity using the Levenberg-Marquardt algorithm [1].
C This step is referred to as the (nonlinear) initialization step.
C
C As last step, the Levenberg-Marquardt algorithm is used again to
C optimize the parameters of the linear part and the static
C nonlinearity as a whole. Therefore, it is necessary to parametrise
C the matrices of the linear part. The output normal form [2]
C parameterisation is used.
C
C The Jacobian is computed analytically, for the nonlinear part, and
C numerically, for the linear part.
C
C REFERENCES
C
C [1] Kelley, C.T.
C Iterative Methods for Optimization.
C Society for Industrial and Applied Mathematics (SIAM),
C Philadelphia (Pa.), 1999.
C
C [2] Peeters, R.L.M., Hanzon, B., and Olivi, M.
C Balanced realizations of discrete-time stable all-pass
C systems and the tangential Schur algorithm.
C Proceedings of the European Control Conference,
C 31 August - 3 September 1999, Karlsruhe, Germany.
C Session CP-6, Discrete-time Systems, 1999.
C
C CONTRIBUTORS
C
C A. Riedel, R. Schneider, Chemnitz University of Technology,
C Oct. 2000, during a stay at University of Twente, NL.
C V. Sima, Research Institute for Informatics, Bucharest, Dec. 2001.
C
C REVISIONS
C
C V. Sima, Research Institute for Informatics, Bucharest, Mar. 2001,
C Mar. 2002, Apr. 2002, Feb. 2004, March 2005, Nov. 2005.
C
C KEYWORDS
C
C Conjugate gradients, least-squares approximation,
C Levenberg-Marquardt algorithm, matrix operations, optimization.
C
C ******************************************************************
C
C .. Parameters ..
DOUBLE PRECISION ZERO
PARAMETER ( ZERO = 0.0D0 )
C The upper triangular part is used in MD03AD;
CHARACTER UPLO
PARAMETER ( UPLO = 'U' )
C For INIT = 'L' or 'B', additional parameters are set:
C The following six parameters are used in the call of IB01AD;
CHARACTER IALG, BATCH, CONCT, CTRL, JOBD, METH
PARAMETER ( IALG = 'Fast QR', BATCH = 'One batch',
$ CONCT = 'Not connect', CTRL = 'Not confirm',
$ JOBD = 'Not MOESP', METH = 'MOESP' )
C The following three parameters are used in the call of IB01BD;
CHARACTER JOB, JOBCK, METHB
PARAMETER ( JOB = 'All matrices',
$ JOBCK = 'No Kalman gain',
$ METHB = 'Combined MOESP+N4SID' )
C The following two parameters are used in the call of IB01CD;
CHARACTER COMUSE, JOBXD
PARAMETER ( COMUSE = 'Use B, D',
$ JOBXD = 'D also' )
C TOLN controls the estimated order in IB01AD (default value);
DOUBLE PRECISION TOLN
PARAMETER ( TOLN = -1.0D0 )
C RCOND controls the rank decisions in IB01AD, IB01BD, and IB01CD
C (default);
DOUBLE PRECISION RCOND
PARAMETER ( RCOND = -1.0D0 )
C .. Scalar Arguments ..
CHARACTER ALG, INIT, STOR
INTEGER INFO, ITMAX1, ITMAX2, IWARN, L, LDU, LDWORK,
$ LDY, LX, M, N, NN, NOBR, NPRINT, NSMP
DOUBLE PRECISION TOL1, TOL2
C .. Array Arguments ..
DOUBLE PRECISION DWORK(*), U(LDU, *), X(*), Y(LDY, *)
INTEGER IWORK(*)
C .. Local Scalars ..
INTEGER AC, BD, BSN, I, IA, IB, IK, INFOL, IQ, IR,
$ IRCND, IRCNDB, IRY, IS, ISAD, ISV, IV, IW1, IW2,
$ IWARNL, IX, IX0, J, JWORK, LDAC, LDR, LIPAR,
$ LNOL, LTHS, ML, MNO, N2, NFEV, NJEV, NS, NSML,
$ NTHS, NX, WRKOPT, Z
LOGICAL CHOL, FULL, INIT1, INIT2
C .. Local Arrays ..
LOGICAL BWORK(1)
INTEGER IPAR(7)
DOUBLE PRECISION RCND(16), SEED(4), WORK(5)
C .. External Functions ..
EXTERNAL LSAME
LOGICAL LSAME
C .. External Subroutines ..
EXTERNAL DCOPY, IB01AD, IB01BD, IB01CD, MD03AD, NF01BA,
$ NF01BB, NF01BU, NF01BV, NF01BW, NF01BX, TB01VD,
$ TB01VY, TF01MX, XERBLA
C .. Intrinsic Functions ..
INTRINSIC INT, MAX, MIN
C ..
C .. Executable Statements ..
C
CHOL = LSAME( ALG, 'D' )
FULL = LSAME( STOR, 'F' )
INIT1 = LSAME( INIT, 'B' ) .OR. LSAME( INIT, 'L' )
INIT2 = LSAME( INIT, 'B' ) .OR. LSAME( INIT, 'S' )
C
ML = M + L
INFO = 0
IWARN = 0
IF ( .NOT.( INIT1 .OR. INIT2 .OR. LSAME( INIT, 'N' ) ) ) THEN
INFO = -1
ELSEIF ( .NOT.( CHOL .OR. LSAME( ALG, 'I' ) ) ) THEN
INFO = -2
ELSEIF ( CHOL .AND. .NOT.( FULL .OR. LSAME( STOR, 'P' ) ) ) THEN
INFO = -3
ELSEIF ( INIT1 .AND. NOBR.LE.0 ) THEN
INFO = -4
ELSEIF ( M.LT.0 ) THEN
INFO = -5
ELSEIF ( L.LT.0 .OR. ( INIT1 .AND. L.EQ.0 ) ) THEN
INFO = -6
ELSEIF ( NSMP.LT.0 .OR.
$ ( INIT1 .AND. NSMP.LT.2*( ML + 1 )*NOBR - 1 ) ) THEN
INFO = -7
ELSEIF ( ( N.LT.0 .AND. .NOT.INIT1 ) .OR.
$ ( ( N.EQ.0 .OR. N.GE.NOBR ) .AND. INIT1 ) ) THEN
INFO = -8
ELSEIF ( NN.LT.0 ) THEN
INFO = -9
ELSEIF ( INIT2 .AND. ( ITMAX1.LT.0 ) ) THEN
INFO = -10
ELSEIF ( ITMAX2.LT.0 ) THEN
INFO = -11
ELSEIF ( LDU.LT.MAX( 1, NSMP ) ) THEN
INFO = -14
ELSEIF ( LDY.LT.MAX( 1, NSMP ) ) THEN
INFO = -16
ELSE
LNOL = L*NOBR - L
MNO = M*NOBR
BSN = NN*( L + 2 ) + 1
NTHS = BSN*L
NSML = NSMP*L
IF ( N.GT.0 ) THEN
LDAC = N + L
ISAD = LDAC*( N + M )
N2 = N*N
END IF
C
C Check the workspace size.
C
JWORK = 0
IF ( INIT1 ) THEN
C Workspace for IB01AD.
JWORK = 2*ML*NOBR*( 2*ML*( NOBR + 1 ) + 3 ) + L*NOBR
IF ( N.GT.0 ) THEN
C Workspace for IB01BD.
IW1 = MAX( 2*LNOL*N + 2*N, LNOL*N + N2 + 7*N, L*NOBR*N +
$ MAX( LNOL*N + 2*N + ( M + ML )*NOBR + L,
$ 2*LNOL*N + N2 + 8*N, N + 4*( MNO + N ) +
$ 1, MNO + 3*N + L ) )
IF ( M.GT.0 ) THEN
IW2 = L*NOBR*N + MNO*LDAC*( M*LDAC + 1 ) +
$ MAX( LDAC**2, 4*M*LDAC + 1 )
ELSE
IW2 = 0
END IF
JWORK = MAX( JWORK,
$ ( 2*ML*NOBR )**2 + ISAD + MAX( IW1, IW2 ) )
C Workspace for IB01CD.
IW1 = NSML*( N + 1 ) + 2*N + MAX( 2*N2, 4*N )
IW2 = N*( N + 1 ) + 2*N +
$ MAX( N*L*( N + 1 ) + 2*N2 + L*N, 4*N )
JWORK = MAX( JWORK, ISAD + 2 + N*( N + 1 + LDAC + M ) +
$ MAX( 5*N, 2, MIN( IW1, IW2 ) ) )
C Workspace for TF01MX.
JWORK = MAX( JWORK, NSML + ISAD + LDAC + 2*N + M )
C Workspace for TB01VD.
JWORK = MAX( JWORK, NSML + ISAD + N +
$ MAX( 1, N2*L + N*L + N,
$ N2 + MAX( N2 + N*MAX( N, L ) +
$ 6*N + MIN( N, L ), N*M ) ) )
END IF
END IF
C
IF ( INIT2 ) THEN
C Workspace for MD03AD (initialization of the nonlinear part).
IF ( CHOL ) THEN
IF ( FULL ) THEN
IW1 = BSN**2
ELSE
IW1 = ( BSN*( BSN + 1 ) )/2
END IF
ELSE
IW1 = 3*BSN + NSMP
END IF
JWORK = MAX( JWORK, NSML +
$ MAX( 5, NSMP + 2*BSN + NSMP*BSN +
$ MAX( 2*NN + BSN, IW1 ) ) )
IF ( N.GT.0 .AND. .NOT.INIT1 ) THEN
C Workspace for TB01VY.
JWORK = MAX( JWORK, NSML + LDAC*( 2*N + M ) + 2*N )
C Workspace for TF01MX.
IF ( M.GT.0 ) THEN
IW1 = N + M
ELSE
IW1 = 0
END IF
JWORK = MAX( JWORK, NSML + ISAD + IW1 + LDAC + N )
END IF
END IF
C
IF ( N.GE.0 ) THEN
C
C Find the number of parameters.
C
LTHS = N*( ML + 1 ) + L*M
NX = NTHS + LTHS
C
IF ( LX.LT.NX ) THEN
INFO = -18
CALL XERBLA( 'IB03AD', -INFO )
RETURN
END IF
C
C Workspace for MD03AD (whole optimization).
C
IF ( M.GT.0 ) THEN
IW1 = LDAC + M
ELSE
IW1 = L
END IF
IW1 = NSML + MAX( 2*NN, ISAD + 2*N + MAX( N*LDAC, IW1 ) )
IF ( CHOL ) THEN
IF ( FULL ) THEN
IW2 = NX**2
ELSE
IW2 = ( NX*( NX + 1 ) )/2
END IF
ELSE
IW2 = 3*NX + NSML
END IF
JWORK = MAX( JWORK,
$ 5, NSML + 2*NX + NSML*( BSN + LTHS ) +
$ MAX( IW1 + NX, NSML + IW1, IW2 ) )
END IF
C
IF ( LDWORK.LT.JWORK ) THEN
INFO = -23
DWORK(1) = JWORK
END IF
END IF
C
IF( INFO.NE.0 ) THEN
CALL XERBLA( 'IB03AD', -INFO )
RETURN
ENDIF
C
C Initialize the pointers to system matrices and save the possible
C seed for random numbers generation.
C
Z = 1
AC = Z + NSML
CALL DCOPY( 4, DWORK, 1, SEED, 1 )
C
WRKOPT = 1
C
IF ( INIT1 ) THEN
C
C Initialize the linear part.
C If N < 0, the order of the system is determined by IB01AD;
C otherwise, the given order will be used.
C The workspace needed is defined for the options set above
C in the PARAMETER statements.
C Workspace: need: 2*(M+L)*NOBR*(2*(M+L)*(NOBR+1)+3) + L*NOBR;
C prefer: larger.
C Integer workspace: M+L. (If METH = 'N', (M+L)*NOBR.)
C
NS = N
IR = 1
ISV = 2*ML*NOBR
LDR = ISV
IF ( LSAME( JOBD, 'M' ) )
$ LDR = MAX( LDR, 3*MNO )
ISV = IR + LDR*ISV
JWORK = ISV + L*NOBR
C
CALL IB01AD( METH, IALG, JOBD, BATCH, CONCT, CTRL, NOBR, M, L,
$ NSMP, U, LDU, Y, LDY, N, DWORK(IR), LDR,
$ DWORK(ISV), RCOND, TOLN, IWORK, DWORK(JWORK),
$ LDWORK-JWORK+1, IWARNL, INFOL )
C
IF( INFOL.NE.0 ) THEN
INFO = 100*INFOL
RETURN
END IF
IF( IWARNL.NE.0 )
$ IWARN = 100*IWARNL
WRKOPT = MAX( WRKOPT, INT( DWORK(JWORK) ) + JWORK - 1 )
IRCND = 0
IF ( LSAME( METH, 'N' ) ) THEN
IRCND = 2
CALL DCOPY( IRCND, DWORK(JWORK+1), 1, RCND, 1 )
END IF
C
IF ( NS.GE.0 ) THEN
N = NS
ELSE
C
C Find the number of parameters.
C
LDAC = N + L
ISAD = LDAC*( N + M )
N2 = N*N
LTHS = N*( ML + 1 ) + L*M
NX = NTHS + LTHS
C
IF ( LX.LT.NX ) THEN
LX = NX
INFO = -18
CALL XERBLA( 'IB03AD', -INFO )
RETURN
END IF
C Workspace for IB01BD.
IW1 = MAX( 2*LNOL*N + 2*N, LNOL*N + N2 + 7*N, L*NOBR*N +
$ MAX( LNOL*N + 2*N + ( M + ML )*NOBR + L,
$ 2*LNOL*N + N2 + 8*N, N + 4*( MNO + N ) + 1,
$ MNO + 3*N + L ) )
IF ( M.GT.0 ) THEN
IW2 = L*NOBR*N + MNO*LDAC*( M*LDAC + 1 ) +
$ MAX( LDAC**2, 4*M*LDAC + 1 )
ELSE
IW2 = 0
END IF
JWORK = ISV + ISAD + MAX( IW1, IW2 )
C Workspace for IB01CD.
IW1 = NSML*( N + 1 ) + 2*N + MAX( 2*N2, 4*N )
IW2 = N*( N + 1 ) + 2*N + MAX( N*L*( N + 1 ) + 2*N2 + L*N,
$ 4*N )
JWORK = MAX( JWORK, ISAD + 2 + N*( N + 1 + LDAC + M ) +
$ MAX( 5*N, 2, MIN( IW1, IW2 ) ) )
C Workspace for TF01MX.
JWORK = MAX( JWORK, NSML + ISAD + LDAC + 2*N + M )
C Workspace for TB01VD.
JWORK = MAX( JWORK, NSML + ISAD + N +
$ MAX( 1, N2*L + N*L + N,
$ N2 + MAX( N2 + N*MAX( N, L ) +
$ 6*N + MIN( N, L ), N*M ) ) )
C Workspace for MD03AD (whole optimization).
IF ( M.GT.0 ) THEN
IW1 = LDAC + M
ELSE
IW1 = L
END IF
IW1 = NSML + MAX( 2*NN, ISAD + 2*N + MAX( N*LDAC, IW1 ) )
IF ( CHOL ) THEN
IF ( FULL ) THEN
IW2 = NX**2
ELSE
IW2 = ( NX*( NX + 1 ) )/2
END IF
ELSE
IW2 = 3*NX + NSML
END IF
JWORK = MAX( JWORK,
$ 5, NSML + 2*NX + NSML*( BSN + LTHS ) +
$ MAX( IW1 + NX, NSML + IW1, IW2 ) )
IF ( LDWORK.LT.JWORK ) THEN
INFO = -23
DWORK(1) = JWORK
CALL XERBLA( 'IB03AD', -INFO )
RETURN
END IF
END IF
C
BD = AC + LDAC*N
IX = BD + LDAC*M
IA = ISV
IB = IA + LDAC*N
IQ = IB + LDAC*M
IF ( LSAME( JOBCK, 'N' ) ) THEN
IRY = IQ
IS = IQ
IK = IQ
JWORK = IQ
ELSE
IRY = IQ + N2
IS = IRY + L*L
IK = IS + N*L
JWORK = IK + N*L
END IF
C
C The workspace needed is defined for the options set above
C in the PARAMETER statements.
C Workspace:
C need: 4*(M+L)*NOBR*(M+L)*NOBR + (N+L)*(N+M) +
C max( LDW1,LDW2 ), where,
C LDW1 >= max( 2*(L*NOBR-L)*N+2*N, (L*NOBR-L)*N+N*N+7*N,
C L*NOBR*N +
C max( (L*NOBR-L)*N+2*N + (2*M+L)*NOBR+L,
C 2*(L*NOBR-L)*N+N*N+8*N,
C N+4*(M*NOBR+N)+1, M*NOBR+3*N+L ) )
C LDW2 >= 0, if M = 0;
C LDW2 >= L*NOBR*N+M*NOBR*(N+L)*(M*(N+L)+1)+
C max( (N+L)**2, 4*M*(N+L)+1 ), if M > 0;
C prefer: larger.
C Integer workspace: MAX(M*NOBR+N,M*(N+L)).
C
CALL IB01BD( METHB, JOB, JOBCK, NOBR, N, M, L, NSMP, DWORK(IR),
$ LDR, DWORK(IA), LDAC, DWORK(IA+N), LDAC,
$ DWORK(IB), LDAC, DWORK(IB+N), LDAC, DWORK(IQ), N,
$ DWORK(IRY), L, DWORK(IS), N, DWORK(IK), N, RCOND,
$ IWORK, DWORK(JWORK), LDWORK-JWORK+1, BWORK,
$ IWARNL, INFOL )
C
IF( INFOL.EQ.-30 ) THEN
INFO = -23
DWORK(1) = DWORK(JWORK)
CALL XERBLA( 'IB03AD', -INFO )
RETURN
END IF
IF( INFOL.NE.0 ) THEN
INFO = 100*INFOL
RETURN
END IF
IF( IWARNL.NE.0 )
$ IWARN = 100*IWARNL
WRKOPT = MAX( WRKOPT, INT( DWORK(JWORK) ) + JWORK - 1 )
IRCNDB = 4
IF ( LSAME( JOBCK, 'K' ) )
$ IRCNDB = IRCNDB + 8
CALL DCOPY( IRCNDB, DWORK(JWORK+1), 1, RCND(IRCND+1), 1 )
IRCND = IRCND + IRCNDB
C
C Copy the system matrices to the beginning of DWORK, to save
C space, and redefine the pointers.
C
CALL DCOPY( ISAD, DWORK(IA), 1, DWORK, 1 )
IA = 1
IB = IA + LDAC*N
IX0 = IB + LDAC*M
IV = IX0 + N
C
C Compute the initial condition of the system. On normal exit,
C DWORK(i), i = JWORK+2:JWORK+1+N*N,
C DWORK(j), j = JWORK+2+N*N:JWORK+1+N*N+L*N, and
C DWORK(k), k = JWORK+2+N*N+L*N:JWORK+1+N*N+L*N+N*M,
C contain the transformed system matrices At, Ct, and Bt,
C respectively, corresponding to the real Schur form of the
C estimated system state matrix A. The transformation matrix is
C stored in DWORK(IV:IV+N*N-1).
C The workspace needed is defined for the options set above
C in the PARAMETER statements.
C Workspace:
C need: (N+L)*(N+M) + N + N*N + 2 + N*( N + M + L ) +
C max( 5*N, 2, min( LDW1, LDW2 ) ), where,
C LDW1 = NSMP*L*(N + 1) + 2*N + max( 2*N*N, 4*N),
C LDW2 = N*(N + 1) + 2*N +
C max( N*L*(N + 1) + 2*N*N + L*N, 4*N);
C prefer: larger.
C Integer workspace: N.
C
JWORK = IV + N2
CALL IB01CD( 'X needed', COMUSE, JOBXD, N, M, L, NSMP,
$ DWORK(IA), LDAC, DWORK(IB), LDAC, DWORK(IA+N),
$ LDAC, DWORK(IB+N), LDAC, U, LDU, Y, LDY,
$ DWORK(IX0), DWORK(IV), N, RCOND, IWORK,
$ DWORK(JWORK), LDWORK-JWORK+1, IWARNL, INFOL )
C
IF( INFOL.EQ.-26 ) THEN
INFO = -23
DWORK(1) = DWORK(JWORK)
CALL XERBLA( 'IB03AD', -INFO )
RETURN
END IF
IF( INFOL.EQ.1 )
$ INFOL = 10
IF( INFOL.NE.0 ) THEN
INFO = 100*INFOL
RETURN
END IF
IF( IWARNL.NE.0 )
$ IWARN = 100*IWARNL
WRKOPT = MAX( WRKOPT, INT( DWORK(JWORK) ) + JWORK - 1 )
IRCND = IRCND + 1
RCND(IRCND) = DWORK(JWORK+1)
C
C Now, save the system matrices and x0 in the final location.
C
IF ( IV.LT.AC ) THEN
CALL DCOPY( ISAD+N, DWORK(IA), 1, DWORK(AC), 1 )
ELSE
DO 5 J = AC + ISAD + N - 1, AC, -1
DWORK(J) = DWORK(IA+J-AC)
5 CONTINUE
END IF
C
C Compute the output of the linear part.
C Workspace: need NSMP*L + (N + L)*(N + M) + 3*N + M + L,
C if M > 0;
C NSMP*L + (N + L)*N + 2*N + L, if M = 0;
C prefer larger.
C
JWORK = IX + N
CALL DCOPY( N, DWORK(IX), 1, X(NTHS+1), 1 )
CALL TF01MX( N, M, L, NSMP, DWORK(AC), LDAC, U, LDU, X(NTHS+1),
$ DWORK(Z), NSMP, DWORK(JWORK), LDWORK-JWORK+1,
$ INFO )
C
C Convert the state-space representation to output normal form.
C Workspace:
C need: NSMP*L + (N + L)*(N + M) + N +
C MAX(1, N*N*L + N*L + N, N*N +
C MAX(N*N + N*MAX(N,L) + 6*N + MIN(N,L), N*M));
C prefer: larger.
C
CALL TB01VD( 'Apply', N, M, L, DWORK(AC), LDAC, DWORK(BD),
$ LDAC, DWORK(AC+N), LDAC, DWORK(BD+N), LDAC,
$ DWORK(IX), X(NTHS+1), LTHS, DWORK(JWORK),
$ LDWORK-JWORK+1, INFOL )
C
IF( INFOL.GT.0 ) THEN
INFO = INFOL + 3
RETURN
END IF
WRKOPT = MAX( WRKOPT, INT( DWORK(JWORK) ) + JWORK - 1 )
C
END IF
C
LIPAR = 7
IW1 = 0
IW2 = 0
C
IF ( INIT2 ) THEN
C
C Initialize the nonlinear part.
C
IF ( .NOT.INIT1 ) THEN
BD = AC + LDAC*N
IX = BD + LDAC*M
C
C Convert the output normal form to state-space model.
C Workspace: need NSMP*L + (N + L)*(2*N + M) + 2*N.
C (NSMP*L locations are reserved for the output of the linear
C part.)
C
JWORK = IX + N
CALL TB01VY( 'Apply', N, M, L, X(NTHS+1), LTHS, DWORK(AC),
$ LDAC, DWORK(BD), LDAC, DWORK(AC+N), LDAC,
$ DWORK(BD+N), LDAC, DWORK(IX), DWORK(JWORK),
$ LDWORK-JWORK+1, INFO )
C
C Compute the output of the linear part.
C Workspace: need NSMP*L + (N + L)*(N + M) + 3*N + M + L,
C if M > 0;
C NSMP*L + (N + L)*N + 2*N + L, if M = 0;
C prefer larger.
C
CALL TF01MX( N, M, L, NSMP, DWORK(AC), LDAC, U, LDU,
$ DWORK(IX), DWORK(Z), NSMP, DWORK(JWORK),
$ LDWORK-JWORK+1, INFO )
END IF
C
C Optimize the parameters of the nonlinear part.
C Workspace:
C need NSMP*L +
C MAX( 5, NSMP + 2*BSN + NSMP*BSN +
C MAX( 2*NN + BSN, DW( sol ) ) ),
C where, if ALG = 'D',
C DW( sol ) = BSN*BSN, if STOR = 'F';
C DW( sol ) = BSN*(BSN+1)/2, if STOR = 'P';
C and DW( sol ) = 3*BSN + NSMP, if ALG = 'I';
C prefer larger.
C
JWORK = AC
WORK(1) = ZERO
CALL DCOPY( 4, WORK(1), 0, WORK(2), 1 )
C
C Set the integer parameters needed, including the number of
C neurons.
C
IPAR(1) = NSMP
IPAR(2) = L
IPAR(3) = NN
C
DO 10 I = 0, L - 1
CALL DCOPY( 4, SEED, 1, DWORK(JWORK), 1 )
IF ( CHOL ) THEN
CALL MD03AD( 'Random initialization', ALG, STOR, UPLO,
$ NF01BA, NF01BV, NSMP, BSN, ITMAX1, NPRINT,
$ IPAR, LIPAR, DWORK(Z), NSMP, Y(1,I+1), LDY,
$ X(I*BSN+1), NFEV, NJEV, TOL1, TOL1,
$ DWORK(JWORK), LDWORK-JWORK+1, IWARNL,
$ INFOL )
ELSE
CALL MD03AD( 'Random initialization', ALG, STOR, UPLO,
$ NF01BA, NF01BX, NSMP, BSN, ITMAX1, NPRINT,
$ IPAR, LIPAR, DWORK(Z), NSMP, Y(1,I+1), LDY,
$ X(I*BSN+1), NFEV, NJEV, TOL1, TOL1,
$ DWORK(JWORK), LDWORK-JWORK+1, IWARNL,
$ INFOL )
END IF
C
IF( INFOL.NE.0 ) THEN
INFO = 10*INFOL
RETURN
END IF
IF ( IWARNL.LT.0 ) THEN
INFO = INFOL
IWARN = IWARNL
GO TO 20
ELSEIF ( IWARNL.GT.0 ) THEN
IF ( IWARN.GT.100 ) THEN
IWARN = MAX( IWARN, ( IWARN/100 )*100 + 10*IWARNL )
ELSE
IWARN = MAX( IWARN, 10*IWARNL )
END IF
END IF
WORK(1) = MAX( WORK(1), DWORK(JWORK) )
WORK(2) = MAX( WORK(2), DWORK(JWORK+1) )
WORK(5) = MAX( WORK(5), DWORK(JWORK+4) )
WORK(3) = WORK(3) + DWORK(JWORK+2)
WORK(4) = WORK(4) + DWORK(JWORK+3)
IW1 = NFEV + IW1
IW2 = NJEV + IW2
10 CONTINUE
C
ENDIF
C
C Main iteration.
C Workspace: need MAX( 5, NFUN + 2*NX + NFUN*( BSN + LTHS ) +
C MAX( LDW1 + NX, NFUN + LDW1, DW( sol ) ) ),
C where NFUN = NSMP*L, and
C LDW1 = NFUN + MAX( 2*NN, (N + L)*(N + M) + 2*N +
C MAX( N*(N + L), N + M + L )),