Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms
Abstract By applying the Kronecker product and vectorization operator, we extend the quasi-minimal residual variant of the biconjugate gradient stabilized (QMRCGSTAB) algorithm for solving the general coupled matrix equations ∑j=1l(Ai,1,jX1Bi,1,j+Ai,2,jX2Bi,2,j+⋯+Ai,l,jXlBi,l,j)=Cifori=1,2,…,l,%$\be...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Hajarian, Masoud [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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| Schlagwörter: |
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| Anmerkung: |
© SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2013 |
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| Übergeordnetes Werk: |
Enthalten in: Computational and applied mathematics - Berlin : Springer, 2003, 33(2013), 2 vom: 10. Aug., Seite 349-362 |
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| Übergeordnetes Werk: |
volume:33 ; year:2013 ; number:2 ; day:10 ; month:08 ; pages:349-362 |
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| DOI / URN: |
10.1007/s40314-013-0065-z |
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| Katalog-ID: |
SPR036715530 |
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| 100 | 1 | |a Hajarian, Masoud |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms |
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| 520 | |a Abstract By applying the Kronecker product and vectorization operator, we extend the quasi-minimal residual variant of the biconjugate gradient stabilized (QMRCGSTAB) algorithm for solving the general coupled matrix equations ∑j=1l(Ai,1,jX1Bi,1,j+Ai,2,jX2Bi,2,j+⋯+Ai,l,jXlBi,l,j)=Cifori=1,2,…,l,%$\begin{aligned} \sum ^l_{j=1} (A_{i,1,j}X_{1}B_{i,1,j}+A_{i,2,j}X_{2}B_{i,2,j}+\cdots +A_{i,l,j}X_{l}B_{i,l,j})=C_i\quad \hbox {for}\quad i=1,2,\ldots ,l, \end{aligned}%$and the periodic coupled matrix equations A1,tXtB1,t+C1,tXt+1D1,t+E1,tYtF1,t=G1,t,A2,tXtB2,t+C2,tXt+1D2,t+E2,tYtF2,t=G2,t,fort=1,2,…,ϕ.%$\begin{aligned} \left\{ \begin{array}{ll} \mathcal A _{1,t}\mathcal X _t\mathcal B _{1,t}+\mathcal C _{1,t}\mathcal X _{t+1}\mathcal D _{1,t}+\mathcal E _{1,t}\mathcal Y _t\mathcal F _{1,t} =\mathcal G _{1,t}, \\ \mathcal A _{2,t}\mathcal X _{t}\mathcal B _{2,t}+\mathcal C _{2,t}\mathcal X _{t+1}\mathcal D _{2,t}+\mathcal E _{2,t}\mathcal Y _t\mathcal F _{2,t} =\mathcal G _{2,t}, \end{array} \right. \quad \hbox {for}\quad t=1,2,\ldots ,\phi . \end{aligned}%$Several numerical examples are given to show the efficiency of the extended QMRCGSTAB algorithms. | ||
| 650 | 4 | |a QMRCGSTAB algorithm |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Lyapunov matrix equation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Sylvester matrix equation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Periodic coupled matrix equations |7 (dpeaa)DE-He213 | |
| 773 | 0 | 8 | |i Enthalten in |t Computational and applied mathematics |d Berlin : Springer, 2003 |g 33(2013), 2 vom: 10. Aug., Seite 349-362 |w (DE-627)47617502X |w (DE-600)2171678-X |x 1807-0302 |7 nnns |
| 773 | 1 | 8 | |g volume:33 |g year:2013 |g number:2 |g day:10 |g month:08 |g pages:349-362 |
| 856 | 4 | 0 | |u https://dx.doi.org/10.1007/s40314-013-0065-z |z lizenzpflichtig |3 Volltext |
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2013 |
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2013 |
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10.1007/s40314-013-0065-z doi (DE-627)SPR036715530 (SPR)s40314-013-0065-z-e DE-627 ger DE-627 rakwb eng Hajarian, Masoud verfasserin aut Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2013 Abstract By applying the Kronecker product and vectorization operator, we extend the quasi-minimal residual variant of the biconjugate gradient stabilized (QMRCGSTAB) algorithm for solving the general coupled matrix equations ∑j=1l(Ai,1,jX1Bi,1,j+Ai,2,jX2Bi,2,j+⋯+Ai,l,jXlBi,l,j)=Cifori=1,2,…,l,%$\begin{aligned} \sum ^l_{j=1} (A_{i,1,j}X_{1}B_{i,1,j}+A_{i,2,j}X_{2}B_{i,2,j}+\cdots +A_{i,l,j}X_{l}B_{i,l,j})=C_i\quad \hbox {for}\quad i=1,2,\ldots ,l, \end{aligned}%$and the periodic coupled matrix equations A1,tXtB1,t+C1,tXt+1D1,t+E1,tYtF1,t=G1,t,A2,tXtB2,t+C2,tXt+1D2,t+E2,tYtF2,t=G2,t,fort=1,2,…,ϕ.%$\begin{aligned} \left\{ \begin{array}{ll} \mathcal A _{1,t}\mathcal X _t\mathcal B _{1,t}+\mathcal C _{1,t}\mathcal X _{t+1}\mathcal D _{1,t}+\mathcal E _{1,t}\mathcal Y _t\mathcal F _{1,t} =\mathcal G _{1,t}, \\ \mathcal A _{2,t}\mathcal X _{t}\mathcal B _{2,t}+\mathcal C _{2,t}\mathcal X _{t+1}\mathcal D _{2,t}+\mathcal E _{2,t}\mathcal Y _t\mathcal F _{2,t} =\mathcal G _{2,t}, \end{array} \right. \quad \hbox {for}\quad t=1,2,\ldots ,\phi . \end{aligned}%$Several numerical examples are given to show the efficiency of the extended QMRCGSTAB algorithms. QMRCGSTAB algorithm (dpeaa)DE-He213 Lyapunov matrix equation (dpeaa)DE-He213 Sylvester matrix equation (dpeaa)DE-He213 Periodic coupled matrix equations (dpeaa)DE-He213 Enthalten in Computational and applied mathematics Berlin : Springer, 2003 33(2013), 2 vom: 10. Aug., Seite 349-362 (DE-627)47617502X (DE-600)2171678-X 1807-0302 nnns volume:33 year:2013 number:2 day:10 month:08 pages:349-362 https://dx.doi.org/10.1007/s40314-013-0065-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2013 2 10 08 349-362 |
| spelling |
10.1007/s40314-013-0065-z doi (DE-627)SPR036715530 (SPR)s40314-013-0065-z-e DE-627 ger DE-627 rakwb eng Hajarian, Masoud verfasserin aut Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2013 Abstract By applying the Kronecker product and vectorization operator, we extend the quasi-minimal residual variant of the biconjugate gradient stabilized (QMRCGSTAB) algorithm for solving the general coupled matrix equations ∑j=1l(Ai,1,jX1Bi,1,j+Ai,2,jX2Bi,2,j+⋯+Ai,l,jXlBi,l,j)=Cifori=1,2,…,l,%$\begin{aligned} \sum ^l_{j=1} (A_{i,1,j}X_{1}B_{i,1,j}+A_{i,2,j}X_{2}B_{i,2,j}+\cdots +A_{i,l,j}X_{l}B_{i,l,j})=C_i\quad \hbox {for}\quad i=1,2,\ldots ,l, \end{aligned}%$and the periodic coupled matrix equations A1,tXtB1,t+C1,tXt+1D1,t+E1,tYtF1,t=G1,t,A2,tXtB2,t+C2,tXt+1D2,t+E2,tYtF2,t=G2,t,fort=1,2,…,ϕ.%$\begin{aligned} \left\{ \begin{array}{ll} \mathcal A _{1,t}\mathcal X _t\mathcal B _{1,t}+\mathcal C _{1,t}\mathcal X _{t+1}\mathcal D _{1,t}+\mathcal E _{1,t}\mathcal Y _t\mathcal F _{1,t} =\mathcal G _{1,t}, \\ \mathcal A _{2,t}\mathcal X _{t}\mathcal B _{2,t}+\mathcal C _{2,t}\mathcal X _{t+1}\mathcal D _{2,t}+\mathcal E _{2,t}\mathcal Y _t\mathcal F _{2,t} =\mathcal G _{2,t}, \end{array} \right. \quad \hbox {for}\quad t=1,2,\ldots ,\phi . \end{aligned}%$Several numerical examples are given to show the efficiency of the extended QMRCGSTAB algorithms. QMRCGSTAB algorithm (dpeaa)DE-He213 Lyapunov matrix equation (dpeaa)DE-He213 Sylvester matrix equation (dpeaa)DE-He213 Periodic coupled matrix equations (dpeaa)DE-He213 Enthalten in Computational and applied mathematics Berlin : Springer, 2003 33(2013), 2 vom: 10. Aug., Seite 349-362 (DE-627)47617502X (DE-600)2171678-X 1807-0302 nnns volume:33 year:2013 number:2 day:10 month:08 pages:349-362 https://dx.doi.org/10.1007/s40314-013-0065-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2013 2 10 08 349-362 |
| allfields_unstemmed |
10.1007/s40314-013-0065-z doi (DE-627)SPR036715530 (SPR)s40314-013-0065-z-e DE-627 ger DE-627 rakwb eng Hajarian, Masoud verfasserin aut Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2013 Abstract By applying the Kronecker product and vectorization operator, we extend the quasi-minimal residual variant of the biconjugate gradient stabilized (QMRCGSTAB) algorithm for solving the general coupled matrix equations ∑j=1l(Ai,1,jX1Bi,1,j+Ai,2,jX2Bi,2,j+⋯+Ai,l,jXlBi,l,j)=Cifori=1,2,…,l,%$\begin{aligned} \sum ^l_{j=1} (A_{i,1,j}X_{1}B_{i,1,j}+A_{i,2,j}X_{2}B_{i,2,j}+\cdots +A_{i,l,j}X_{l}B_{i,l,j})=C_i\quad \hbox {for}\quad i=1,2,\ldots ,l, \end{aligned}%$and the periodic coupled matrix equations A1,tXtB1,t+C1,tXt+1D1,t+E1,tYtF1,t=G1,t,A2,tXtB2,t+C2,tXt+1D2,t+E2,tYtF2,t=G2,t,fort=1,2,…,ϕ.%$\begin{aligned} \left\{ \begin{array}{ll} \mathcal A _{1,t}\mathcal X _t\mathcal B _{1,t}+\mathcal C _{1,t}\mathcal X _{t+1}\mathcal D _{1,t}+\mathcal E _{1,t}\mathcal Y _t\mathcal F _{1,t} =\mathcal G _{1,t}, \\ \mathcal A _{2,t}\mathcal X _{t}\mathcal B _{2,t}+\mathcal C _{2,t}\mathcal X _{t+1}\mathcal D _{2,t}+\mathcal E _{2,t}\mathcal Y _t\mathcal F _{2,t} =\mathcal G _{2,t}, \end{array} \right. \quad \hbox {for}\quad t=1,2,\ldots ,\phi . \end{aligned}%$Several numerical examples are given to show the efficiency of the extended QMRCGSTAB algorithms. QMRCGSTAB algorithm (dpeaa)DE-He213 Lyapunov matrix equation (dpeaa)DE-He213 Sylvester matrix equation (dpeaa)DE-He213 Periodic coupled matrix equations (dpeaa)DE-He213 Enthalten in Computational and applied mathematics Berlin : Springer, 2003 33(2013), 2 vom: 10. Aug., Seite 349-362 (DE-627)47617502X (DE-600)2171678-X 1807-0302 nnns volume:33 year:2013 number:2 day:10 month:08 pages:349-362 https://dx.doi.org/10.1007/s40314-013-0065-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2013 2 10 08 349-362 |
| allfieldsGer |
10.1007/s40314-013-0065-z doi (DE-627)SPR036715530 (SPR)s40314-013-0065-z-e DE-627 ger DE-627 rakwb eng Hajarian, Masoud verfasserin aut Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2013 Abstract By applying the Kronecker product and vectorization operator, we extend the quasi-minimal residual variant of the biconjugate gradient stabilized (QMRCGSTAB) algorithm for solving the general coupled matrix equations ∑j=1l(Ai,1,jX1Bi,1,j+Ai,2,jX2Bi,2,j+⋯+Ai,l,jXlBi,l,j)=Cifori=1,2,…,l,%$\begin{aligned} \sum ^l_{j=1} (A_{i,1,j}X_{1}B_{i,1,j}+A_{i,2,j}X_{2}B_{i,2,j}+\cdots +A_{i,l,j}X_{l}B_{i,l,j})=C_i\quad \hbox {for}\quad i=1,2,\ldots ,l, \end{aligned}%$and the periodic coupled matrix equations A1,tXtB1,t+C1,tXt+1D1,t+E1,tYtF1,t=G1,t,A2,tXtB2,t+C2,tXt+1D2,t+E2,tYtF2,t=G2,t,fort=1,2,…,ϕ.%$\begin{aligned} \left\{ \begin{array}{ll} \mathcal A _{1,t}\mathcal X _t\mathcal B _{1,t}+\mathcal C _{1,t}\mathcal X _{t+1}\mathcal D _{1,t}+\mathcal E _{1,t}\mathcal Y _t\mathcal F _{1,t} =\mathcal G _{1,t}, \\ \mathcal A _{2,t}\mathcal X _{t}\mathcal B _{2,t}+\mathcal C _{2,t}\mathcal X _{t+1}\mathcal D _{2,t}+\mathcal E _{2,t}\mathcal Y _t\mathcal F _{2,t} =\mathcal G _{2,t}, \end{array} \right. \quad \hbox {for}\quad t=1,2,\ldots ,\phi . \end{aligned}%$Several numerical examples are given to show the efficiency of the extended QMRCGSTAB algorithms. QMRCGSTAB algorithm (dpeaa)DE-He213 Lyapunov matrix equation (dpeaa)DE-He213 Sylvester matrix equation (dpeaa)DE-He213 Periodic coupled matrix equations (dpeaa)DE-He213 Enthalten in Computational and applied mathematics Berlin : Springer, 2003 33(2013), 2 vom: 10. Aug., Seite 349-362 (DE-627)47617502X (DE-600)2171678-X 1807-0302 nnns volume:33 year:2013 number:2 day:10 month:08 pages:349-362 https://dx.doi.org/10.1007/s40314-013-0065-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2013 2 10 08 349-362 |
| allfieldsSound |
10.1007/s40314-013-0065-z doi (DE-627)SPR036715530 (SPR)s40314-013-0065-z-e DE-627 ger DE-627 rakwb eng Hajarian, Masoud verfasserin aut Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2013 Abstract By applying the Kronecker product and vectorization operator, we extend the quasi-minimal residual variant of the biconjugate gradient stabilized (QMRCGSTAB) algorithm for solving the general coupled matrix equations ∑j=1l(Ai,1,jX1Bi,1,j+Ai,2,jX2Bi,2,j+⋯+Ai,l,jXlBi,l,j)=Cifori=1,2,…,l,%$\begin{aligned} \sum ^l_{j=1} (A_{i,1,j}X_{1}B_{i,1,j}+A_{i,2,j}X_{2}B_{i,2,j}+\cdots +A_{i,l,j}X_{l}B_{i,l,j})=C_i\quad \hbox {for}\quad i=1,2,\ldots ,l, \end{aligned}%$and the periodic coupled matrix equations A1,tXtB1,t+C1,tXt+1D1,t+E1,tYtF1,t=G1,t,A2,tXtB2,t+C2,tXt+1D2,t+E2,tYtF2,t=G2,t,fort=1,2,…,ϕ.%$\begin{aligned} \left\{ \begin{array}{ll} \mathcal A _{1,t}\mathcal X _t\mathcal B _{1,t}+\mathcal C _{1,t}\mathcal X _{t+1}\mathcal D _{1,t}+\mathcal E _{1,t}\mathcal Y _t\mathcal F _{1,t} =\mathcal G _{1,t}, \\ \mathcal A _{2,t}\mathcal X _{t}\mathcal B _{2,t}+\mathcal C _{2,t}\mathcal X _{t+1}\mathcal D _{2,t}+\mathcal E _{2,t}\mathcal Y _t\mathcal F _{2,t} =\mathcal G _{2,t}, \end{array} \right. \quad \hbox {for}\quad t=1,2,\ldots ,\phi . \end{aligned}%$Several numerical examples are given to show the efficiency of the extended QMRCGSTAB algorithms. QMRCGSTAB algorithm (dpeaa)DE-He213 Lyapunov matrix equation (dpeaa)DE-He213 Sylvester matrix equation (dpeaa)DE-He213 Periodic coupled matrix equations (dpeaa)DE-He213 Enthalten in Computational and applied mathematics Berlin : Springer, 2003 33(2013), 2 vom: 10. Aug., Seite 349-362 (DE-627)47617502X (DE-600)2171678-X 1807-0302 nnns volume:33 year:2013 number:2 day:10 month:08 pages:349-362 https://dx.doi.org/10.1007/s40314-013-0065-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2013 2 10 08 349-362 |
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English |
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Enthalten in Computational and applied mathematics 33(2013), 2 vom: 10. Aug., Seite 349-362 volume:33 year:2013 number:2 day:10 month:08 pages:349-362 |
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Enthalten in Computational and applied mathematics 33(2013), 2 vom: 10. Aug., Seite 349-362 volume:33 year:2013 number:2 day:10 month:08 pages:349-362 |
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QMRCGSTAB algorithm Lyapunov matrix equation Sylvester matrix equation Periodic coupled matrix equations |
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Computational and applied mathematics |
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Hajarian, Masoud @@aut@@ |
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2013-08-10T00:00:00Z |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR036715530</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230328165856.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201007s2013 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s40314-013-0065-z</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR036715530</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s40314-013-0065-z-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hajarian, Masoud</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2013</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2013</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract By applying the Kronecker product and vectorization operator, we extend the quasi-minimal residual variant of the biconjugate gradient stabilized (QMRCGSTAB) algorithm for solving the general coupled matrix equations ∑j=1l(Ai,1,jX1Bi,1,j+Ai,2,jX2Bi,2,j+⋯+Ai,l,jXlBi,l,j)=Cifori=1,2,…,l,%$\begin{aligned} \sum ^l_{j=1} (A_{i,1,j}X_{1}B_{i,1,j}+A_{i,2,j}X_{2}B_{i,2,j}+\cdots +A_{i,l,j}X_{l}B_{i,l,j})=C_i\quad \hbox {for}\quad i=1,2,\ldots ,l, \end{aligned}%$and the periodic coupled matrix equations A1,tXtB1,t+C1,tXt+1D1,t+E1,tYtF1,t=G1,t,A2,tXtB2,t+C2,tXt+1D2,t+E2,tYtF2,t=G2,t,fort=1,2,…,ϕ.%$\begin{aligned} \left\{ \begin{array}{ll} \mathcal A _{1,t}\mathcal X _t\mathcal B _{1,t}+\mathcal C _{1,t}\mathcal X _{t+1}\mathcal D _{1,t}+\mathcal E _{1,t}\mathcal Y _t\mathcal F _{1,t} =\mathcal G _{1,t}, \\ \mathcal A _{2,t}\mathcal X _{t}\mathcal B _{2,t}+\mathcal C _{2,t}\mathcal X _{t+1}\mathcal D _{2,t}+\mathcal E _{2,t}\mathcal Y _t\mathcal F _{2,t} =\mathcal G _{2,t}, \end{array} \right. \quad \hbox {for}\quad t=1,2,\ldots ,\phi . \end{aligned}%$Several numerical examples are given to show the efficiency of the extended QMRCGSTAB algorithms.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">QMRCGSTAB algorithm</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Lyapunov matrix equation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Sylvester matrix equation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Periodic coupled matrix equations</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Computational and applied mathematics</subfield><subfield code="d">Berlin : Springer, 2003</subfield><subfield code="g">33(2013), 2 vom: 10. 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Hajarian, Masoud |
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Hajarian, Masoud misc QMRCGSTAB algorithm misc Lyapunov matrix equation misc Sylvester matrix equation misc Periodic coupled matrix equations Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms |
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Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms QMRCGSTAB algorithm (dpeaa)DE-He213 Lyapunov matrix equation (dpeaa)DE-He213 Sylvester matrix equation (dpeaa)DE-He213 Periodic coupled matrix equations (dpeaa)DE-He213 |
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Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms |
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Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms |
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10.1007/s40314-013-0065-z |
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solving the general coupled and the periodic coupled matrix equations via the extended qmrcgstab algorithms |
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Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms |
| abstract |
Abstract By applying the Kronecker product and vectorization operator, we extend the quasi-minimal residual variant of the biconjugate gradient stabilized (QMRCGSTAB) algorithm for solving the general coupled matrix equations ∑j=1l(Ai,1,jX1Bi,1,j+Ai,2,jX2Bi,2,j+⋯+Ai,l,jXlBi,l,j)=Cifori=1,2,…,l,%$\begin{aligned} \sum ^l_{j=1} (A_{i,1,j}X_{1}B_{i,1,j}+A_{i,2,j}X_{2}B_{i,2,j}+\cdots +A_{i,l,j}X_{l}B_{i,l,j})=C_i\quad \hbox {for}\quad i=1,2,\ldots ,l, \end{aligned}%$and the periodic coupled matrix equations A1,tXtB1,t+C1,tXt+1D1,t+E1,tYtF1,t=G1,t,A2,tXtB2,t+C2,tXt+1D2,t+E2,tYtF2,t=G2,t,fort=1,2,…,ϕ.%$\begin{aligned} \left\{ \begin{array}{ll} \mathcal A _{1,t}\mathcal X _t\mathcal B _{1,t}+\mathcal C _{1,t}\mathcal X _{t+1}\mathcal D _{1,t}+\mathcal E _{1,t}\mathcal Y _t\mathcal F _{1,t} =\mathcal G _{1,t}, \\ \mathcal A _{2,t}\mathcal X _{t}\mathcal B _{2,t}+\mathcal C _{2,t}\mathcal X _{t+1}\mathcal D _{2,t}+\mathcal E _{2,t}\mathcal Y _t\mathcal F _{2,t} =\mathcal G _{2,t}, \end{array} \right. \quad \hbox {for}\quad t=1,2,\ldots ,\phi . \end{aligned}%$Several numerical examples are given to show the efficiency of the extended QMRCGSTAB algorithms. © SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2013 |
| abstractGer |
Abstract By applying the Kronecker product and vectorization operator, we extend the quasi-minimal residual variant of the biconjugate gradient stabilized (QMRCGSTAB) algorithm for solving the general coupled matrix equations ∑j=1l(Ai,1,jX1Bi,1,j+Ai,2,jX2Bi,2,j+⋯+Ai,l,jXlBi,l,j)=Cifori=1,2,…,l,%$\begin{aligned} \sum ^l_{j=1} (A_{i,1,j}X_{1}B_{i,1,j}+A_{i,2,j}X_{2}B_{i,2,j}+\cdots +A_{i,l,j}X_{l}B_{i,l,j})=C_i\quad \hbox {for}\quad i=1,2,\ldots ,l, \end{aligned}%$and the periodic coupled matrix equations A1,tXtB1,t+C1,tXt+1D1,t+E1,tYtF1,t=G1,t,A2,tXtB2,t+C2,tXt+1D2,t+E2,tYtF2,t=G2,t,fort=1,2,…,ϕ.%$\begin{aligned} \left\{ \begin{array}{ll} \mathcal A _{1,t}\mathcal X _t\mathcal B _{1,t}+\mathcal C _{1,t}\mathcal X _{t+1}\mathcal D _{1,t}+\mathcal E _{1,t}\mathcal Y _t\mathcal F _{1,t} =\mathcal G _{1,t}, \\ \mathcal A _{2,t}\mathcal X _{t}\mathcal B _{2,t}+\mathcal C _{2,t}\mathcal X _{t+1}\mathcal D _{2,t}+\mathcal E _{2,t}\mathcal Y _t\mathcal F _{2,t} =\mathcal G _{2,t}, \end{array} \right. \quad \hbox {for}\quad t=1,2,\ldots ,\phi . \end{aligned}%$Several numerical examples are given to show the efficiency of the extended QMRCGSTAB algorithms. © SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2013 |
| abstract_unstemmed |
Abstract By applying the Kronecker product and vectorization operator, we extend the quasi-minimal residual variant of the biconjugate gradient stabilized (QMRCGSTAB) algorithm for solving the general coupled matrix equations ∑j=1l(Ai,1,jX1Bi,1,j+Ai,2,jX2Bi,2,j+⋯+Ai,l,jXlBi,l,j)=Cifori=1,2,…,l,%$\begin{aligned} \sum ^l_{j=1} (A_{i,1,j}X_{1}B_{i,1,j}+A_{i,2,j}X_{2}B_{i,2,j}+\cdots +A_{i,l,j}X_{l}B_{i,l,j})=C_i\quad \hbox {for}\quad i=1,2,\ldots ,l, \end{aligned}%$and the periodic coupled matrix equations A1,tXtB1,t+C1,tXt+1D1,t+E1,tYtF1,t=G1,t,A2,tXtB2,t+C2,tXt+1D2,t+E2,tYtF2,t=G2,t,fort=1,2,…,ϕ.%$\begin{aligned} \left\{ \begin{array}{ll} \mathcal A _{1,t}\mathcal X _t\mathcal B _{1,t}+\mathcal C _{1,t}\mathcal X _{t+1}\mathcal D _{1,t}+\mathcal E _{1,t}\mathcal Y _t\mathcal F _{1,t} =\mathcal G _{1,t}, \\ \mathcal A _{2,t}\mathcal X _{t}\mathcal B _{2,t}+\mathcal C _{2,t}\mathcal X _{t+1}\mathcal D _{2,t}+\mathcal E _{2,t}\mathcal Y _t\mathcal F _{2,t} =\mathcal G _{2,t}, \end{array} \right. \quad \hbox {for}\quad t=1,2,\ldots ,\phi . \end{aligned}%$Several numerical examples are given to show the efficiency of the extended QMRCGSTAB algorithms. © SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2013 |
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| title_short |
Solving the general coupled and the periodic coupled matrix equations via the extended QMRCGSTAB algorithms |
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https://dx.doi.org/10.1007/s40314-013-0065-z |
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| doi_str |
10.1007/s40314-013-0065-z |
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2024-07-03T19:14:38.287Z |
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| score |
7.4018583 |