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Highlights from
LYAPACK
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% Low rank Cholesky factor Newton method (explicit version LRCF-NM and
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...
% LRCF-ADI for solving the stable Lyapunov equation:
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...
% Using updated QR factorizations, this routine computes efficiently
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as_l(tr,X)
% Solves linear systems with the real, symmetric, negative definite matrix A,
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as_l_d
% Deletes the global data that has been generated by 'as_l_i'.
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as_l_i
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as_m(tr,X)
% Evaluates matrix-matrix products with the real, symmetric matrix A,
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as_m_d
% Deletes the global data that has been generated by 'as_m_i'.
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as_m_i(A)
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as_pre(A,B,C)
% Preprocessing of the system
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as_pst(X,iprm)
% Postprocessing. This routine is the counterpart of 'as_pre'. It
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as_s(tr,X,i)
% Solves shifted linear systems with the real, symmetric, negative definite
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as_s_d(p)
% Deletes the global data that has been generated by 'as_s_i'.
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as_s_i(p)
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au_l(tr,X)
% Solves linear systems with the real matrix A or its transposed A':
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au_l_d
% Deletes the global data that has been generated by 'au_l_i'.
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au_l_i
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au_m(tr,X)
% Evaluates matrix-matrix products with the real matrix A or its
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au_m_d
% Deletes the global data that has been generated by 'au_m_i'.
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au_m_i(A)
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au_pre(A,B,C)
% Preprocessing of the system
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au_pst(X,iprm)
% Postprocessing. This routine is the counterpart of 'au_pre'. It
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au_qmr_ilu_l(tr,X)
% Solves linear systems with the real matrix A or its transpose A' using
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au_qmr_ilu_l_d
% Deletes the global data that has been generated by 'au_qmr_ilu_l_i'.
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au_qmr_ilu_l_i
% Generates the data used in 'au_qmr_ilu_l'. Data are stored in global
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au_qmr_ilu_m(tr,X)
% Evaluates matrix-matrix products with the real matrix A or its
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au_qmr_ilu_m_d
% Deletes the global data that has been generated by 'au_qmr_ilu_m_i'.
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au_qmr_ilu_m_i(A,mc,max_it_qm...
% Generates the data used in 'au_qmr_ilu_m'. Data are stored in global
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au_qmr_ilu_s(tr,X,i)
% Solves shifted linear systems with the matrix A or its transpose A' by
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au_qmr_ilu_s_d(p)
% Deletes the global data that has been generated by 'au_qmr_ilu_s_i'
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au_qmr_ilu_s_i(p)
% Generates the data used in 'au_qmr_ilu_s'. Data are stored in global
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au_s(tr,X,i)
% Solves shifted linear systems with the real matrix A or its
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au_s_d(p)
% Deletes the global data that has been generated by 'au_s_i'.
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au_s_i(p)
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fdm_2d_matrix(n0,fx_str,fy_st...
% Generates the stiffness matrix A for the finite difference
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fdm_2d_vector(n0,f_str)
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lp_arn_m(name,Bf,Kf,k,r)
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lp_arn_p(name,Bf,Kf,k,r)
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lp_dspmr(name,B,C,ZB,ZC,max_o...
% Model reduction method DSPMR (Dominant Subspace Projection Model
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lp_e(i1,i2,i3,i4,i5,i6,i7,i8,...
% Auxiliary routine for the execution of strings with MATLAB
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lp_gnorm(Gs,m,q)
% Given the transfer function sample matrix Gs, which contains
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lp_lgfrq(min_freq,max_freq,no...
% Delivers a vector of "frequency sampling points" which are
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lp_lrsrm(name,B,C,ZB,ZC,max_o...
% Model reduction method LRSRM (Low Rank Square Root Method)
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lp_mnmx(rw,l0)
% Suboptimal solution of the ADI minimax problem. The delivered parameter
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lp_nrm( tp, name, Bf, Kf, G, ...
% Computes efficiently either of the following norms provided that
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lp_para(name,Bf,Kf,l0,kp,km,b...
% Estimation of suboptimal ADI shift parameters for the matrix
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lp_prm(A,E)
% Reordering of SPARSE standard/generalized systems
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lp_rcnrm( name, B, C0, R, Z )
% Computes efficiently the Riccati norm when the approximate solution
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lp_s(p,set)
% Computation of the maximal magnitude of the rational ADI function over
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lp_trfia(freq,A,B,C,D,E)
% Computes the transfer function for systems
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msns_l(tr,X)
% Solves linear systems with the symmetric, negative definite matrix A,
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msns_l_d
% Deletes the global data that has been generated by 'msns_l_i'.
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msns_l_i
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msns_m(tr,X)
% Evaluates matrix-matrix products with the symmetric matrix A,
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msns_m_d
% Deletes the global data that has been generated by 'msns_m_i'.
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msns_m_i(M,MU,N)
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msns_pre(M,N,B,C)
% Preprocessing of the system
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msns_pst(Z,MU,iprm)
% Postprocessing. This routine is the counterpart of 'msns_pre'. It
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msns_s(tr,X,i)
% Solves shifted linear systems with the symmetric, negative definite
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msns_s_d(p)
% Deletes the global data that has been generated by 'msns_s_i'.
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msns_s_i(p)
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munu_l(tr,X)
% Solves linear systems with the real matrix A or its transposed A':
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munu_l_d
% Deletes the global data that has been generated by 'munu_l_i'.
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munu_l_i
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munu_m(tr,X)
% Evaluates matrix-matrix products with the real matrix A or its
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munu_m_d
% Deletes the global data that has been generated by 'munu_m_i'.
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munu_m_i(M,ML,MU,N)
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munu_pre(M,N,B,C)
% Preprocessing of the system
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munu_pst(ZB,ZC,ML,MU,iprm)
% Postprocessing. This routine is the counterpart of preprocessing
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munu_s(tr,X,i)
% Solves shifted linear systems with the real matrix A or its
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munu_s_d(p)
% Deletes the global data that has been generated by 'munu_s_i'.
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munu_s_i(p)
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demo_l1.m
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demo_m1.m
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demo_m2.m
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demo_r1.m
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demo_u1.m
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demo_u2.m
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demo_u3.m
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lstartup.m
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View all files
LYAPACK
by Volker Mehrmann
28 Aug 2000
LYAPACK toolbox provides solutions for certain large scale problems related to Lyapunov equations.
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| File Information |
| Description |
LYAPACK is a MATLAB toolbox for the solution of certain large scale problems in control theory, which are closely related to Lyapunov equations. In contrast to the 'lyap' and 'dlyap' command in the MATLAB Control toolbox it uses iterative algorithms and is intended for large, sparse problems. |
| Required Products |
Control System Toolbox
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| MATLAB release |
MATLAB 5.3 (R11)
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| Comments and Ratings (1) |
| 15 Sep 2002 |
Dale Clifford
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