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            | FULL TEXT IN RUSSIAN  
 Mekhatronika, Avtomatizatsiya, Upravlenie, 2015, vol. 16, no. 9, pp.  579—584DOI: 10.17587/mau.16.579-584
 
 An Effective Algorithm for  Realization of the Vector Fitting Method for the Identification Tasks of the  Dynamical Systems                 M. M. Gourary, gourary@ippm.ru, M. M. Zharov, zarov@ippm.ru, S. G. Rusakov, rusakov@ippm.ru, S. L. Ulyanov, ulyas@ippm.ru, L. S. Khodosh, khod@ippm.ru Institute for Design Problems in  Microelectronics of the Russian Academy of Sciences (IPPM RAS), Moscow, 124365,  Russian Federation
 
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            | Corresponding author: Zharov Mikhail M., Ph.  D., Leading Researcher, Institute for Design Problems in Microelectronics of  the Russian Academy of Sciences (IPPM RAS), Moscow, 124365, Russian Federation,  e-mail: zarov@ippm.ru Received on April 23, 2015 Accepted on May 15, 2015
                 A new algorithm for the least squares (LS)  solutions within the Vector Fitting (VF) method is proposed in the paper. The  algorithm is based on QR-factorization, which exploits the specific structure  of the VF matrix. Numerical experiments confirmed an essential reduction of the  computational efforts. Besides, the new algorithm ensures a better accuracy and  requires considerably less memory than the standard Matlab sparse solver. The  special form of LS matrix (left part of the matrix is block-diagonal with  identical blocks) in VF problem allowed us to propose a more effective linear  solver, than the standard one. The efficiency of the new algorithm is achieved  due to replacement of the full matrix QR factorization by the following  sequence of operations: QR factorization of the block; orthogonalization of the  right part of the matrix with respect to the obtained block of Q matrix; QR  factorization of the orthogonalized right part of the matrix. It was experimentally  demonstrated that in order to ensure sufficient accuracy of the solver it was  necessary to perform reorthogonalization of Q matrix of the right part of LS  matrix and to perform QR factorizations with column permutation. Testing of the  developed solver and its comparison with the standard solver was done for two  data sets. The testing results showed that the new solver allowed us to reduce  CPU time by the factor up to 50 for sufficiently large sizes of LS system. In  most cases the new solver ensures less value of the residual norm than the  standard solver and a better accuracy. The advantages of the new solver become  even more impressive with an increase of the size of the system.                 Keywords: vector-fitting, macromodel,  least-squares method, transfer function, linear solver, sparse matrix,  frequency response 
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            | For citation:Gourary M. M., Zharov M. M., Rusakov S. G.,  Ulyanov S. L., Khodosh L. S. An Effective Algorithm for Realization of the  Vector Fitting Method for the Identification Tasks of the Dynamical Systems,  Mekhatronika, Avtomatizatsiya, Upravlenie, 2015, vol. 16, no. 9, pp. 579—584.
 DOI: 10.17587/mau.16. 579-584
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