Developing iterative algorithms to solve Sylvester tensor equations

Abstract This paper is concerned with solving high order Sylvester tensor equation arising in control theory. We propose the tensor forms of the bi-conjugate gradient and bi-conjugate residual methods for solving the tensor equation. To improve their performance, two preconditioned iterative algorithms based on the nearest Kronecker product are developed for finding its solution. We also prove that the proposed algorithms are convergent to an exact solution within finite iteration steps for any initial tensor in the absence of round-off errors. At last, some numerical examples are provided to illustrate the feasibility and validity of the algorithms proposed.

[1]  Amy Nicole Langville,et al.  A Kronecker product approximate preconditioner for SANs , 2004, Numer. Linear Algebra Appl..

[2]  Ben-Wen Li,et al.  Schur-decomposition for 3D matrix equations and its application in solving radiative discrete ordinates equations discretized by Chebyshev collocation spectral method , 2010, J. Comput. Phys..

[3]  Amy Nicole Langville,et al.  Testing the Nearest Kronecker Product Preconditioner on Markov Chains and Stochastic Automata Networks , 2004, INFORMS J. Comput..

[4]  Arnold Neumaier,et al.  Global Optimization by Multilevel Coordinate Search , 1999, J. Glob. Optim..

[5]  Masoud Hajarian,et al.  Symmetric solutions of the coupled generalized Sylvester matrix equations via BCR algorithm , 2016, J. Frankl. Inst..

[6]  M. Ng,et al.  Solving sparse non-negative tensor equations: algorithms and applications , 2015 .

[7]  P. C. Robinson,et al.  A numerical study of various algorithms related to the preconditioned conjugate gradient method , 1985 .

[8]  Masoud Hajarian,et al.  Solving tensor E-eigenvalue problem faster , 2020, Appl. Math. Lett..

[9]  Gene H. Golub,et al.  Hermitian and Skew-Hermitian Splitting Methods for Non-Hermitian Positive Definite Linear Systems , 2002, SIAM J. Matrix Anal. Appl..

[10]  Changfeng Ma,et al.  A modified CG algorithm for solving generalized coupled Sylvester tensor equations , 2020, Appl. Math. Comput..

[11]  Lars Grasedyck,et al.  F ¨ Ur Mathematik in Den Naturwissenschaften Leipzig a Projection Method to Solve Linear Systems in Tensor Format a Projection Method to Solve Linear Systems in Tensor Format , 2022 .

[12]  Anthony T. Chronopoulos,et al.  Interval tensors and their application in solving multi-linear systems of equations , 2020, Comput. Math. Appl..

[13]  Delin Chu,et al.  Numerically Reliable Computing for the Row by Row Decoupling Problem with Stability , 2001, SIAM J. Matrix Anal. Appl..

[14]  Qing-Wen Wang,et al.  Numerical algorithms for solving discrete Lyapunov tensor equation , 2020, J. Comput. Appl. Math..

[15]  Ting-Zhu Huang,et al.  BiCR-type methods for families of shifted linear systems , 2014, Comput. Math. Appl..

[16]  M. Hajarian Convergence properties of BCR method for generalized Sylvester matrix equation over generalized reflexive and anti-reflexive matrices , 2018 .

[17]  Linzhang Lu,et al.  A projection method and Kronecker product preconditioner for solving Sylvester tensor equations , 2012, Science China Mathematics.

[18]  Eric de Sturler,et al.  Recycling BiCG with an Application to Model Reduction , 2010, SIAM J. Sci. Comput..

[19]  Farid Saberi Movahed,et al.  A tensor format for the generalized Hessenberg method for solving Sylvester tensor equations , 2020, J. Comput. Appl. Math..

[20]  L. Qi,et al.  Tensor Analysis: Spectral Theory and Special Tensors , 2017 .

[21]  Yousef Saad,et al.  Iterative methods for sparse linear systems , 2003 .

[22]  M. Hajarian Reflexive periodic solutions of general periodic matrix equations , 2019, Mathematical Methods in the Applied Sciences.

[23]  Yi-Fen Ke FINITE ITERATIVE ALGORITHM FOR THE COMPLEX GENERALIZED SYLVESTER TENSOR EQUATIONS , 2020 .

[24]  Shao-Liang Zhang,et al.  GPBi-CG: Generalized Product-type Methods Based on Bi-CG for Solving Nonsymmetric Linear Systems , 1997, SIAM J. Sci. Comput..

[25]  Tamara G. Kolda,et al.  Tensor Decompositions and Applications , 2009, SIAM Rev..

[26]  Gerard L. G. Sleijpen,et al.  BiCR variants of the hybrid BiCG methods for solving linear systems with nonsymmetric matrices , 2010, J. Comput. Appl. Math..

[27]  Masoud Hajarian,et al.  Conjugate gradient-like methods for solving general tensor equation with Einstein product , 2020, J. Frankl. Inst..

[28]  Linzhang Lu,et al.  A Gradient Based Iterative Solutions for Sylvester Tensor Equations , 2013 .

[29]  M. Sugihara,et al.  An extension of the conjugate residual method to nonsymmetric linear systems , 2009 .

[30]  Alaeddin Malek,et al.  A mixed collocation-finite difference method for 3D microscopic heat transport problems , 2008 .

[31]  C. Lanczos Solution of Systems of Linear Equations by Minimized Iterations1 , 1952 .

[32]  T. Chan,et al.  An analysis of the composite step biconjugate gradient method , 1993 .

[33]  Masoud Hajarian,et al.  Developing Bi-CG and Bi-CR Methods to Solve Generalized Sylvester-transpose Matrix Equations , 2014, Int. J. Autom. Comput..

[34]  Changfeng Ma,et al.  Global least squares methods based on tensor form to solve a class of generalized Sylvester tensor equations , 2020, Appl. Math. Comput..

[35]  Liqun Qi,et al.  Tensor Eigenvalues and Their Applications , 2018 .

[36]  Delin Chu,et al.  Numerical Computation for Orthogonal Low-Rank Approximation of Tensors , 2019, SIAM J. Matrix Anal. Appl..

[37]  F. Beik,et al.  Residual norm steepest descent based iterative algorithms for Sylvester tensor equations , 2015 .

[38]  Masoud Hajarian,et al.  Convergence of a transition probability tensor of a higher‐order Markov chain to the stationary probability vector , 2016, Numer. Linear Algebra Appl..

[39]  S. Karimi,et al.  Global least squares method based on tensor form to solve linear systems in Kronecker format , 2018, Trans. Inst. Meas. Control.

[40]  Qing-Wen Wang,et al.  Extending BiCG and BiCR methods to solve the Stein tensor equation , 2019, Comput. Math. Appl..

[41]  Randolph E. Bank,et al.  A composite step bi-conjugate gradient algorithm for nonsymmetric linear systems , 1994, Numerical Algorithms.

[42]  Changfeng Ma,et al.  An iterative algorithm to solve the generalized Sylvester tensor equations , 2018, Linear and Multilinear Algebra.

[43]  Fatemeh Panjeh Ali Beik,et al.  On the Krylov subspace methods based on tensor format for positive definite Sylvester tensor equations , 2016, Numer. Linear Algebra Appl..

[44]  D. Bernstein,et al.  The optimal projection equations for reduced-order state estimation , 1985 .

[45]  M. Chu,et al.  Convergence analysis of an SVD-based algorithm for the best rank-1 tensor approximation , 2018, Linear Algebra and its Applications.

[46]  Brett W. Bader,et al.  The TOPHITS Model for Higher-Order Web Link Analysis∗ , 2006 .

[47]  Wen-Wei Lin,et al.  Robust Partial Pole Assignment for Vibrating Systems With Aerodynamic Effects , 2006, IEEE Transactions on Automatic Control.

[48]  Yu Guan,et al.  SVD-Based Algorithms for the Best Rank-1 Approximation of a Symmetric Tensor , 2018, SIAM J. Matrix Anal. Appl..

[49]  Khalide Jbilou,et al.  On global iterative schemes based on Hessenberg process for (ill-posed) Sylvester tensor equations , 2020, J. Comput. Appl. Math..

[50]  Volker Mehrmann,et al.  Disturbance Decoupling for Descriptor Systems by State Feedback , 2000, SIAM J. Control. Optim..

[51]  Lars Grasedyck,et al.  Existence and Computation of Low Kronecker-Rank Approximations for Large Linear Systems of Tensor Product Structure , 2004, Computing.

[52]  Liqun Qi,et al.  Eigenvalues of a real supersymmetric tensor , 2005, J. Symb. Comput..

[53]  C. Loan,et al.  Approximation with Kronecker Products , 1992 .

[54]  Masoud Hajarian,et al.  Computing symmetric solutions of general Sylvester matrix equations via Lanczos version of biconjugate residual algorithm , 2018, Comput. Math. Appl..