LEADER 03492nam 22005655 450 001 9910279754703321 005 20231128174452.0 010 $a3-319-69107-4 024 7 $a10.1007/978-3-319-69107-7 035 $a(CKB)4100000004243470 035 $a(DE-He213)978-3-319-69107-7 035 $a(MiAaPQ)EBC6310592 035 $a(PPN)227402669 035 $a(EXLCZ)994100000004243470 100 $a20180514d2017 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aScientific Computing $eVol. II - Eigenvalues and Optimization /$fby John A. Trangenstein 205 $a1st ed. 2017. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017. 215 $a1 online resource (XXVI, 600 p. 645 illus., 111 illus. in color.) 225 1 $aTexts in Computational Science and Engineering,$x1611-0994 ;$v19 311 $a3-319-69106-6 327 $a1. Eigenvalues and Eigenvectors -- 2. Iterative Linear Algebra -- 3. Nonlinear Systems -- 4. Constrained Optimization -- References -- Author Index. 330 $aThis is the second of three volumes providing a comprehensive presentation of the fundamentals of scientific computing. This volume discusses more advanced topics than volume one, and is largely not a prerequisite for volume three. This book and its companions show how to determine the quality of computational results, and how to measure the relative efficiency of competing methods. Readers learn how to determine the maximum attainable accuracy of algorithms, and how to select the best method for computing problems. This book also discusses programming in several languages, including C++, Fortran and MATLAB. There are 49 examples, 110 exercises, 66 algorithms, 24 interactive JavaScript programs, 77 references to software programs and 1 case study. Topics are introduced with goals, literature references and links to public software. There are descriptions of the current algorithms in LAPACK, GSLIB and MATLAB. This book could be used for a second course in numerical methods, for either upper level undergraduates or first year graduate students. Parts of the text could be used for specialized courses, such as nonlinear optimization or iterative linear algebra. 410 0$aTexts in Computational Science and Engineering,$x1611-0994 ;$v19 606 $aComputer science$xMathematics 606 $aDifferential equations 606 $aMathematical optimization 606 $aComputational Mathematics and Numerical Analysis$3https://scigraph.springernature.com/ontologies/product-market-codes/M1400X 606 $aOrdinary Differential Equations$3https://scigraph.springernature.com/ontologies/product-market-codes/M12147 606 $aOptimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26008 615 0$aComputer science$xMathematics. 615 0$aDifferential equations. 615 0$aMathematical optimization. 615 14$aComputational Mathematics and Numerical Analysis. 615 24$aOrdinary Differential Equations. 615 24$aOptimization. 676 $a512.9436 700 $aTrangenstein$b J. A$g(John Arthur),$f1949-$4aut$4http://id.loc.gov/vocabulary/relators/aut$0506734 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910279754703321 996 $aScientific Computing$91563009 997 $aUNINA