scholarly journals Iterative solution of two matrix equations

1999 ◽  
Vol 68 (228) ◽  
pp. 1589-1604 ◽  
Author(s):  
Chun-Hua Guo ◽  
Peter Lancaster
Filomat ◽  
2012 ◽  
Vol 26 (4) ◽  
pp. 809-826 ◽  
Author(s):  
Caiqin Song ◽  
Guoliang Chen ◽  
Xiangyun Zhang

This note studies the iterative solution to the coupled quaternion matrix equations [?pi=1 T1i(Xi), ?pi=1 T2(Xi)... ?pi=1 Tp(Xi)] = [M1, M2,???, Mp], where Tsi,s = 1, 2,???, p; is a linear operator from Qmi,xni onto Qps?qs, Ms ? Qps?qs,s = 1, 2,???, p.i = 1, 2,???, p, by making use of a generalization of the classical complex conjugate graduate iterative algorithm. Based on the proposed iterative algorithm, the existence conditions of solution to the above coupled quaternion matrix equations can be determined. When the considered coupled quaternion matrix equations is consistent, it is proven by using a real inner product in quaternion space as a tool that a solution can be obtained within finite iterative steps for any initial quaternion matrices [X1(0),???,Xp (0)] in the absence of round-off errors and the least Frobenius norm solution can be derived by choosing a special kind of initial quaternion matrices. Furthermore, the optimal approximation solution to a given quaternion matrix can be derived. Finally, a numerical example is given to show the efficiency of the presented iterative method.


2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Hongcai Yin ◽  
Huamin Zhang

By analyzing the eigenvalues of the related matrices, the convergence analysis of the least squares based iteration is given for solving the coupled Sylvester equationsAX+YB=CandDX+YE=Fin this paper. The analysis shows that the optimal convergence factor of this iterative algorithm is 1. In addition, the proposed iterative algorithm can solve the generalized Sylvester equationAXB+CXD=F. The analysis demonstrates that if the matrix equation has a unique solution then the least squares based iterative solution converges to the exact solution for any initial values. A numerical example illustrates the effectiveness of the proposed algorithm.


1972 ◽  
Vol 13 (2) ◽  
pp. 241-255 ◽  
Author(s):  
J. J. Koliha

In this paper we deal with a linear equation Au = f in a Hilbert space using a general iterative method with a constant iterative operator for the approximate solution. The method has been studied in many papers [1, 2, 4, 9, 13, 14] and thoroughly treated by Householder [3] for matrix equations and by Petryshyn [7] for operator equations in considerably general and unified manner.


2016 ◽  
Vol 40 (1) ◽  
pp. 341-347 ◽  
Author(s):  
Ahmed ME Bayoumi ◽  
Mohamed A Ramadan

In this paper, we present an accelerated gradient-based iterative algorithm for solving extended Sylvester–conjugate matrix equations. The idea is from the gradient-based method introduced in Wu et al. ( Applied Mathematics and Computation 217(1): 130–142, 2010a) and the relaxed gradient-based algorithm proposed in Ramadan et al. ( Asian Journal of Control 16(5): 1–8, 2014) and the modified gradient-based algorithm proposed in Bayoumi (PhD thesis, Ain Shams University, 2014). The convergence analysis of the algorithm is investigated. We show that the iterative solution converges to the exact solution for any initial value provided some appropriate assumptions be made. A numerical example is given to illustrate the effectiveness of the proposed method and to test its efficiency and accuracy compared with an existing one presented in Wu et al. (2010a), Ramadan et al. (2014) and Bayoumi (2014).


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