几类约束矩阵方程问题的理论与计算
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
约束矩阵方程问题是指在一定的约束矩阵集合中求矩阵方程(组)的解.其研究是近年来数值代数研究领域的重要课题.本文研究以下几类特殊约束矩阵方程问题的理论与计算.
     1.两类线性约束矩阵方程问题及其最佳逼近问题的迭代算法
     提出了求线性矩阵方程组:A1XB1=C1,A2XB2=C2的(最小二乘)双对称解的迭代算法;从算子角度,将十余种常见的矩阵结构约束(如对称、中心对称、自反等)划归为一类特殊的算子约束.针对一般形式的线性矩阵方程组,提出了求这一类特定算子约束(最小二乘)解的迭代算法.在不计舍入误差的前提下,所提出的算法均可在有限步内获得上述线性矩阵方程(组)相应的约束(最小二乘)解,并可解决其最佳逼近问题.
     2.非线性矩阵方程:Xs+A*X-1A=Q的Hermitian正定解
     深入研究了非线性矩阵方程:Xs+A*X-tA=Q(s,t为正整数)的定解理论和数值算法.利用矩阵分解原理给出了方程存在Hermitian正定解的两个充分必要条件.给出了方程仅有两个解的充分条件及解的计算公式.研究了AQ(?)=Q(?)A情形下,方程可解的必要条件和解的特性.分析了固定点迭代算法的收敛性,给出了单调收敛条件.此外还考虑了s≥1,0     3.非线性矩阵方程:Xs-A*X-1A=Q的Hermitian正定解
     研究了非线性矩阵方程:Xs-A*X-1A=Q (s,t为正整数)的Hermitian正定解.证明了解的存在性.给出了方程存在唯一解的充分条件.获得了解范围的最新估计.进行了解的扰动分析,导出了一般解和唯一解的扰动界.
     4.非对称代数Riccati方程的极小非负解
     分析了当非对称代数Riccati方程的四个系数矩阵构成一个非奇异M-矩阵或奇异不可约M-矩阵时,方程极小非负解的敏感性.基于不变子空间的扰动性质,导出了极小非负解在任意酉不变范数意义下的扰动界,并获得了条件数的显式表达式.
     5.TLS问题和LS问题解的相关量比较
     在TLS问题和LS问题解残量的比较基础上,在更一般情形下,对TLS问题和LS问题解的加权残量进行了比较.导出了TLS解、改进的LS解及普通LS解加权残量之间的误差界,进一步完善了已有的相关结果.
The constrained matrix equation problem is to find solutions of a matrix equation (or a system of matrix equations) in a constrained matrix set. The research of it has been an important topic in the field of numerical algebra in recent years. In this thesis, theory and computation of some special constrained matrix equation problems are studied.
     1. Iterative algorithms for solving two classes of constrained matrix equation problems and associated optimal approximation problems
     An Iterative algorithms for the (least squares) bisymmetric solutions of the matrix equations A1XB1=C1,A2XB2=C2 is proposed. In the sight of operator, more than ten kinds of common constraints on the structure of matrices (such as symmetric constraint, centrosymmetric constraint, reflexive constraint and so on) are reduced to a kind of special operator constraint. Then an iterative method is constructed to find the (least squares) solutions of the general system of linear matrix equations with this operator constraint. By the proposed iterative algorithms, the constrained solutions above can be obtained in finite iteration steps in the absence of round-off errors. Moreover, the associated optimal approximation problems can also be solved.
     2.Hermitian positive definite solutions of the nonlinear matrix equation Xs+ A*X-tA=Q
     The solvability and numerical algorithms for the nonlinear matrix equation Xs+ A*X-tA=Q are investigated deeply, where s and t are positive integers. Two necessary and sufficient conditions for the existence of a Hermitian positive definite solution are derived by using matrix decomposition principle. Necessary conditions for the existence of the Hermitian positive definite solutions of the matrix equation Xs+A*X-tA=Q with the case AQ1/2=Q1/2A are studied. Based on the convergence analysis of a fixed-point iteration, some monotonically convergent conditions of the iteration are given. Besides, the matrix equation with two cases:s≥1,0     3. Hermitian positive definite solutions of the nonlinear matrix equation Xs-A*X-tA=Q
     The Hermitian positive definite solutions of the nonlinear matrix equation Xs-A*X-tA=Q are studied, where s and t are positive integers. The existence of a Her-mitian positive definite solution is proved. A sufficient condition for the equation to have a unique Hermitian positive definite solution is given. Some new estimates of the Her-mitian positive definite solutions are obtained. Moreover, two perturbation bounds for a Hermitian positive definite solution and the unique solution of the matrix equation are derived respectively.
     4. Perturbation analysis of the minimal nonnegative solution of the nonsymmet-ric algebraic Riccati equation
     The sensitivity analysis of the minimal nonnegative solution of the nonsymmetric algebraic Riccati equation whose four coefficient matrices form a nonsingular M-matrix or an irreducible singular M-matrix is considered. Based on perturbation properties of invariant subspace, some sharp perturbation bounds for the minimal nonnegative solution of the matrix equation for any unitary invariant norm are derived. In addition, explicit expressions of the condition number for the minimal nonnegative solution are obtained.
     5. Comparison of the squared residuals of the TLS and the LS problems
     Based on the comparison of the squared residuals of the Total Least Squares (TLS) and the Least Squares (LS) problems, the weighted squared residuals of the TLS and the LS problems are compared. Bounds of difference between the weighted squared residuals of the TLS, modified LS, and ordinary LS solutions are derived, which extend the existing related results.
引文
[1]Q. Alfio, S. Riccardo, S.Fausto, Numerical Mathematics, Springer-Verlag, Berlin, 2000.
    [2]W. N. Anderson, T. D. Morley, G. E. Trapp, Positive solutions to X=A-BX-1B*, Linear Algebra Appl.,1990,134:53-62.
    [3]A. Antoniou, W. S. Lu, Practical Optimization:Algorithm and Engineering Appli-cations, Chap.2, Springer, New York,2007.
    [4]Z. Z. Bai, Y. H. Gao, L. Z. Lu, Fast iterative schemes for nonsymmetric algebraic Riccati equations arising from transport theory, SIAMJ. Sci. Comput.,2008,30:804-818.
    [5]A. Ben-Israel, T. N. E. Greville, Generalized Inverse:Theory and Applications, Sec-ond Ed., Wiley, New York,2003.
    [6]M.Benzi, G. H. Golub, J. Liesen, Numerical solution of saddle point problems, Acta Numerica,2005:1-137.
    [7]R. Bhatia, Matrix analysis, Gradueta Text in Mathmematics, Spring, Berlin,1997.
    [8]P. Bhimasankaram, Common solutions to the linear matrix equations AX=B, CX= D and EXF=G,Sankhya Ser.A,1976,38:404-409.
    [9]X. W. Chang, J.S. Wang, The symmetric solution of the matrix equations AX+YA-C,AXAT+BYBT=C, and (ATXA,BTXB)=(C,D), Linear Algebra Appl.,1993, 179:171-189.
    [10]J. L. Chen, X. H. Chen, Special Matrices, Tsinghua University Press, Beijing,2001.
    [11]X. Chen, W. Li, On the matrix equation X+A*X-1A=P:solution and perturbation analysis, Math. Num. Sin.,2005,27:303-310 (in Chinese).
    [12]Chu, Symmetric solutions of linear matrix equations by matrix decompositions, Lin-ear Algebra Appl.,1989,119:35-50.
    [13]H. Dai, On the symmetric solutions of linear matrix equations, Linear Algebra Appl., 1990,131:1-7.
    [14]M. Dehghan, M. Hajarian, An iterative algorithm for solving a pair of matrix equa-tions AYB=E, CYD=F over generalized centro-symmetric matrices, Comput. Math. Appl.,2008,56:3246-3260.
    [15]Y. B. Deng, Z. Z. Bai, Y. H. Gao, Iterative orthogonal direction methods for Her-mitian minimum norm solutions of two consistent matrix equations, Numer. Linear Algebra Appl.,2006,13:801-823.
    [16]S. Du, J. Hou, Positive definite solutions of operator equations Xm+A*X-nA=I, Linear and Multilinear Algebra,2003,51:163-173.
    [17]X. Duan, A. Liao, On the existence of Hermitian positive definite solutions of the matrix equation Xs+A*X-1A=Q, Linear Algebra Appl.,2008,429:673-687.
    [18]S. M. El-Sayed, Two iteration processes for computing positive definite solutions of the equation X-A*X-nA=Q, Comput. Math. Appl.,2001,41:579-588.
    [19]S. M. El-Sayed, A. M. Al-Dbiban, On positive definite solutions of the nonlinear matrix equations X+A*X-nA=I, Appl. Math. Comput.,2004,151:533-541.
    [20]S.M.El-Sayed, M. El-Alem, Some properties for the existence of a positive definite solution of matrix equation X+A*X-2m A=I, Appl. Math. Comput.,2002,128:99-108.
    [21]S.M. El-Sayed, M. G. Petkov, Iterative methods for nonlinear matrix equation X+ A*X-αA=I(α>0), Linear Algebra Appl.,2005,403:45-52.
    [22]S.M.El-Sayed,A.C.M.Ran, On an iterative methods for solving a class of nonlinear matrix equations, SIAM J.Matrix Anal Appl,2001,23:632-645.
    [23]J. C. Engwerda, On the existence of a positive definite solution of the matrix equa-tion X+AX-1A=I, Linear Algebra Appl,1993,194:91-108.
    [24]J. C. Engwerda, A. C. M. Ran, A. L. Rijkeboer, Necessary and sufficient conditions for the existence of a positive definite solution of the matrix equation X+A*X-1A=Q, Linear Algebra Appl.,1993,186:255-275.
    [25]A. Ferrante, B. C. Levy, Hermitian solutions of the equation X=Q+NX-1N,Linear Algebra Appl.,1996,247:359-373.
    [26]S. Fital, C. Guo, A note on the fixed-point iteration for the matrix equations X± A*X-1A=1, Linear Algebra Appl.,2008,429:2098-2112.
    [27]T. Furuta, Operator inequalities associated with Holder-McCarthy and kantorovich inequalities,J.Inequal. Appl.,1998,6:137-148.
    [28]Z. Gajic, M. Qureshi. Lyapunov Matrix Equation in System Stability and Cotrol, Academic Press, New York,1995.
    [29]G. H. Golub, C. F. van Loan, Matrix Computation, Third Edition, John. Hopk. Univ. Press,1996.
    [30]G. H. Golub, C. F. Van Loan, An analysis of the total least squares problem, SIAM J. Numer. Anal.,1980,17:883-893.
    [31]G. H. Golub, S. Nash, C. Vanloan, A Hessenberg-Schur method for the problem AX+XB=C, IEEE Trans. Auto. Control.,1979,24:909-913.
    [32]W. L. Green, E.Kamen, Stabilization of linear systems over a commutative normed algebra with applications to spatially distributed parameter dependent systems, SIAM J. Control Optim.,1985,23:1-18.
    [33]C. Guo, P. Lancaster, Iterative solution of two matrix equations, Math. Comput., 1999,68:1589-1603.
    [34]C. H. Guo, Nonsymmetric algebraic Riccati equations and Wiener-Hopf factoriza-tion for M-matrices,SIAMJ. Matrix Anal Appl.,2001,23:225-242.
    [35]C. H. Guo, A note on the minimal nonnegative solution of a nonsymmetric algebraic Riccati equation, Linear Algebra Appl.,2002,357:299-302.
    [36]C. H. Guo, Efficient methods for solving a nonsymmetric algebraic Riccati equation arising in stochastic fluid models, J. Comput. Appl. Math.,2006,192:353-373.
    [37]C. H. Guo, A. J. Laub, On the iterative solution of a class of nonsymmetric algebraic Riccati equations, SIAMJ. Matrix Anal.Appl.,2000,22:376-391.
    [38]C. H. Guo, N. J.Highan, Iterative solution of a nonsysmetric algebraic Riccati equa-tion, SIAMJ. MatrixAnalAppl,2007,29:396-412.
    [39]C. H. Guo, B. Iannazzo, B. Meini, On the doubling algorithm for a (shifted) nonsym-metric algebraic Riccati equation, SIAMJ. Matrix Anal. Appl.,2007,29:1083-1100.
    [40]X. X. Guo, Z. Z. Bai, On the minimal nonnegative solution of nonsymmetric alge-braic Riccati equation, J. Comput Math.,2005,23:305-320.
    [41]X. X. Guo, W. W. Lin, S. F. Xu, A structure-preserving doubling algorithm for nonsymmetric algebraic Riccati equation, Numer. Math.,2006,103:393-402.
    [42]V.I. Hasanov, Positive definite solutions of the matrix equations X±A*X-qA=Q, Linear Algebra Appl,2005,404:166-182.
    [43]V. I. Hasanov, S. M. El-sayed, On the positive definite solutions of nonlinear matrix equation X+A*X-δA=Q, Linear Algebra Appl.,2006,412:154-160.
    [44]V. I. Hasanov, I. G. Ivanov, Positive definite solutions of the equation X+A*X-nA= I, Lecture Notes in Computer Science, Numerical Analysis and its applications 2000, Springer-Verlag,2001:377-384.
    [45]V. I. Hasanov, I. G. Ivanov, Solutions and perturbation estimates for the matrix equa-tions X±A*X-nA=Q,Appl. Math. Comput.,2004,156:513-525.
    [46]V.I.Hasanov, I. G. Ivanov, On the matrix equation X-A*X-nA=I, Appl. Math. Comput.,2005,168:1340-1356.
    [47]V. I. Hasanov, I. G. Ivanov, On two perturbation estimates of the extreme solutions to the equations X±A*X-1A=Q, Linear Algebra Appl,2006,413:81-92.
    [48]N. J. Higham, Computing a nearest symmetric positive semidefinite matrix, Linear Algebra Appl.,1988,103:103-118.
    [49]R. A. Horn, C. R. Johnson, Topics in Matrix Analysis, Cambridge University Press, New York,1991.
    [50]J. J. Hou, Z. Y. Peng, X. L. Zhang, An iterative method for the least square symmet-ric solution of matrix equation AXB=C,Numer. Algor.,2006,42:181-192.
    [51]G. X. Huang, F. Yin, K. Guo, An iterative method for the skew-symmetric solution and the optimal approximate solution of the matrix equation AXB=C, J. Comput. Appl. Math.,2008,212:231-244.
    [52]S. Van Huffel, J. Vandewalle, Analysis of the total least squares problem and its use in parameter estimation, Ph.D.Dissertation, ESATLab., Dept. Electr. Eng., K. U. Leuven, Belgium,1987.
    [53]S. Van Huffel, J. Vandewalle, Analysis and solution of the nongeneric total least squares problem, SIAMJ. Matrix Anal. Appl.,1988,9(3):360-372.
    [54]S. Van Huffel, J. Vandewalle, Algebraic connections between the least squares and total least squares problems, Numer.Math.,1989,55:431-449.
    [55]I.G. Ivanov, On positive definite solutions of the family of matrix equations X+ A*X-nA=Q,J. Comput. Appl. Math.,2006,193:277-301.
    [56]I. G. Ivanov, S. M. El-sayed, Properties of positive definite solutions of the equation X+A*X-2A=I, Linear Algebra Appl.,1998,279:303-316.
    [57]I.G. Ivanov, V. I. Hasanov, B. V. Minchev, On matrix equations X±A*X-2A=I, Linear Algebra Appl.,2001,326:27-44.
    [58]I. G. Ivanov, V.I.Hasanov, F.Uhlig, Improved methods and starting values to solve the matrix equations X±*X-1A=I iteratively,Math. Comput.,2004,74:263-278.
    [59]K. T. Jeseph, Inverse eigenvalue problem in structural design, AIAA J.,1992,30: 2890-2896.
    [60]Z. Jiang, Q. Lu, On optimal approximation of a matrix under a spectral restriction, Math. Numer. Sin.,1986,8:47-52.
    [61]J. Juang, Existence of algebraic matrix Riccati equations arising in transport theory, Linear Algebra Appl.,1995,230:89-100.
    [62]J. Juang, W. W. Lin, Nonsymmetric algebraic Riccati equations and Hamilton-like matrices, SIAMJ. Matrix Anal. Appl.,1998,20:228-243.
    [63]C. Khatri, S. Mitra, Hermitian and nonnegative definite solution of linear matrix equations, SIAM J. Appl. Math.,1976,31:579-585.
    [64]Y. Lei, A. P. Liao, A minimal residual algorithm for the inconsistent matrix equation AXB=C over symmetric matrices, Appl. Math. Comput.,2007,188(1):499-513.
    [65]B. C. Levy, R. Frezza, A. J. Krener, Modeling and estimation of discretetime Gaus-sian reciprocal processes, IEEE Trans. Automat. Control,1990,35:1013-1023.
    [66]F. L. Li, X. Y. Hu, L. Zhang, The generalized anti-reflexive solutions for a class of matrix equations BX=C,XD=E, Comput. Appl. Math.,2008,27:31-46.
    [67]A. Liao, On positive definite solutions of the matrix equation X+A*X-nA=I, Numer. Math.:J. Chin. Univ.,2004,26:156-161.
    [68]A. P. Liao, Y. Lei, Optimal approximate solution of the matrix equation AXB=C over symmetric matrices,J.Comput. Math.,2007,25(5):543-552.
    [69]X. Liu, H. Gao, On the positive definite solutions of the equations±ATX-tA=In, Linear Algebra Appl.,2003,368:83-97.
    [70]刘新国,关于TLS问题的可解性及扰动分析,应用数学学报,1996,19:254-262.
    [71]刘永辉,魏木生,关于TLS和LS问题的比较,计算数学,2003,25:479-492.
    [72]L. Z. Lu, Solution form and simple iteration of a nonsymmetric algebraic Riccati equation arising in transport theory, SIAM J. Matrix Anal. Appl.,2005,26:679-685.
    [73]T. Meng, Experimental design and decision support, in:Leondes(Ed.), Expert Sys-tem, the Technology of Knowledge Management and Decision Making for the 21st Century. Vol.1,Academic Press,2001.
    [74]B. Meini, Efficient computation of the extreme solutions of X+A*X-1A=Q and X-A*X-1A=Q,Math. Comput.,2001,71:1189-1204.
    [75]S. K. Mitra, Common solutions to a pair of linear matrix equations A1XB1= C1,A2XB2=C2,Proc. Cambridge Philos. Soc.,1973,74:213-216.
    [76]S. K. Mitra, A pair of simultaneous linear matrix equations and a matrix program-ming problem, Linear Algebra Appl.,131(1990) 97-123.
    [77]S. K. Mitra, The matrix equations AX=C,XB=D, Linear Algebra Appl.,1984, 59:171-181.
    [78]A. Navarra, P.L. Odell, D. M. Young, A representation of the general common solution to the matrix equationsA1AXB1=C1,A2XB2=C2 with applications, Comput. Math. Appl.,2001,41:929-935.
    [79]D. V. Ouellette, Schur complements and statistics, Linear Algebra Appl.,1981,36: 187-295.
    [80]C. C. Paige, M. A. Saunders, Toward a generalized value decomposition,SIAM J. Numer. Anal,1981,18:398-405.
    [81]M.Parodi, La localisation des valeurs caracterisiques desmatrices etses applica-tions, Gauthiervillars, Paris,1959.
    [82]Z. H. Peng, X. Y. Hu, L. Zhang, The bisymmetric solutions of the matrix equation A1XB1+A2XB2+…+AlXBl=C and its optimal approximation, Linear Algebra Appl.,2007,426:583-595.
    [83]Z. H. Peng, X. Y.Hu, L. Zhang, An efficient algorithm for the least-squares reflexive solution of the matrix equation A1XB1=C1,A2XB2=C2,Appl. Math. Comput., 2006,181:988-999.
    [84]Y. X. Peng, X. Y. Hu, L. Zhang, An iterative method for symmetric solutions and optimal approximation solution of the system of matrix equations, Appl. Math. Com-put.,2006,183:1127-1137.
    [85]Y. X. Peng, X. Y. Hu, L. Zhang, The reflexive and anti-reflexive solutions of the matrix equation AHXB=C,J. Comput. Appl. Math.,2007,200:749-760.
    [86]X. Y. Peng, X. Y. Hu, L. Zhang, The orthogonal-symmetric or orthogonal-anti-symmetric least-square solutions of the matrix equation, Chinese J. Engi. Math., 2006,23(6):1048-1052.
    [87]Z. Y. Peng, An ierative method for the least squares symmetric solution of the linear matrix equation AXB=C,Appl. Math. Comput.,2005,17:711-723.
    [88]Z. Y. Peng, X. Y. Hu, L. Zhang, The inverse problem of bisymmetric matrices, Numer. Linear Algebra Appl.,2004,1:59-73.
    [89]Z. Peng, S. M. El-Sayed, X. Zhang, Iterative methods for the extremal positive so-lution of the matrix equation X+A*X-αA=Q, J. Comput. Appl. Math.,2007,200: 520-527.
    [90]R. Penrose, On best approximate solutions of linear matrix equation, Proc. Cam-bridge Philos. Soc.,1956,52:17-19.
    [91]F. X. Piao, Q. L. Zhang, Z. F. Wang, The solution to matrix equation AX+XTC=B, J. Fran. Inst.,2007,344:1056-1062.
    [92]Y. Y. Qiu, Z. Y. Zhang, J.F. Lu, The matrix equations AX=B,XC=D with PX=sXP constraint, Appl. Math. Comput.,2007,189:1428-1434.
    [93]Y. Y. Qiu, Z. Y. ZHang, J.F. Lu, Matrix iterative solutions to the least squares problem of BXAT=F with some linear constraints, Appl. Math. Comput.,2007, 185:284-300.
    [94]A. C. M. Ran, M. C. B. Reurings, On the nonlinear matrix equation X+A*??(X)A= Q:solutions and perturbation theory, Linear Algebra Appl.,2002,346:15-26.
    [95]J. R. Rice, A theory of condition, J. SIAM Numer. Anal.,1996,3:287-310.
    [96]L. C. G. Roges, Fluid models in queueing theory and Wiener-Hopf factorization of Markov chains, Annl. Appl. Prob.,1994,4:390-413.
    [97]L. C. G. Roges, Z. Shi, Computing the invariant law of a fluid model, J. Appl. Prob., 1994,31:885-896.
    [98]Y. Saad, Iterative methods for sparse linear systems,2nd edition, SIAM, Philadel-phia,2003.
    [99]X. P. Sheng, G. L. Chen, A finite iterative method for solving a pair of linear matrix equations (AXB,CXD)=(E,F),Appl. Math. Comput.,2007,189:1350-1358.
    [100]N. Shinozaki, M. Sibuya, Consistency of a pair of matrix equations with an appli-cation, Kieo Eng. Rep.,1974,27:141-146.
    [101]G. W. Stewart, Error bounds for approximate invariant subspace of closed linear operators, SIAMJ. Numer. Anal.,1971,8:796-808.
    [102]Y. F. Su, G. L. Chen, Iterative methods for solving linear matrix equation and linear matrix system, Int. J. Comput. Math.,2010,87(4):763-774A.
    [103]J. G. Sun, Matrix Perturbation Analysis, Science Press, Beijing,2001(in Chinese).
    [104]J. G.Sun, Perturbation analysis of algebraic Riccati equations, Technical Report UMINF 02.03, Department of Computing Science, Umea Univ.,2002.
    [105]M.H. Wang, X.H. Cheng, M.S. Wei, Iterative algorithms for solving the matrix equation AXB+CXTD=E,Appl. Math. Comput.,2007,187:622-629.
    [106]J. W. van der Woude, Freeback decoupling and stabilization for linear systems with multiple exogenous variables, Ph,D.Thesis,1987:85-199.
    [107]M. Wei, Algebraic relations between the total least squares and least squares prob-lems with more than one solution,Numer. Math.,1992,62:123-148.
    [108]M. Wei, The analysis for the total least squares problem with more than one solu-tion, SIAMJ. Matrix Anal. Appl,1992,13:746-763.
    [109]魏木生,关于TLS和LS解的扰动分析,计算数学,1998,20:267-278.
    [110]魏木生,广义最小二乘问题的理论与计算,科学出版社,2006:84-146.
    [111]M. Wei, G. Majda, On the accuracy of the least squares and the total least squares methods, Numer. Math.,J.Chinese Universities(English series),1994,3:135-153.
    [112]魏木生,朱超,关于TLS问题,计算数学,2002,24:345-352.
    [113]Y. Yang, The iterative method for solving nonlinear matrix equation Xs+A*X-1A= Q,Appl. Math. Comput.,2007,188:46-53.
    [114]Y. X. Yuan, On the two class of best approximation problems, Math. Numer. Sinica,2001,23:-436.
    [115]Y. X. Yuan, Least squares solutions of matrix equation AXB=E,CXD=F, J. East China Shipbuilding Inst,2004,18:29-31.
    [116]Y. X. Yuan, H. Dai, Generalized reflexive solutions of the matrix equation AXB= D and associated optimal approximation problem, Comput. Math. Appl.,2009,56: 643-649.
    [117]X. Zhan, Computing the extremal positive definite solution of a matrix equa-tion,SIAMJ.Sci.Comput,1996,17:1167-1174.
    [118]X. Zhan, J. Xie, On the matrix equation X+ATX-1A=I, Linear Algebra Appl., 1996,247:337-345.
    [119]J. C. Zhang, S. Z. Zhou, X. Y. Hu, The (P,Q) generalized reflexive and anti-reflexive solutions of the matrix equation AX=B,Appl. Math. Comput.2009,209:254-258.
    [120]Y. Zhang, On Hermitian positive solutions of the matrix equation X+A*X-2A=I, Linear Algebra Appl.,2003,372:295-304.
    [121]M. D. Zoltowski, Generalized minimum norm and constrained total least squares with applications to array processing, San Diego.SPIE Signal Processing Ⅲ,1988, 975:78-85.