LEADER 00944nam a2200253 i 4500 001 991002014059707536 005 20020503160058.0 008 010315s1964 it ||| | ita 035 $ab10304575-39ule_inst 035 $aEXGIL96076$9ExL 040 $aBiblioteca Interfacoltà$bita 082 0 $a914.57541 100 1 $aCiccarese, Michele$0452348 245 10$aBrindisi turistica :$bfaro di civiltà /$cMichele Ciccarese 260 $aNovoli :$bGreco,$c1964 300 $a136 p. :$bill. 650 4$aBrindisi 907 $a.b10304575$b02-04-14$c27-06-02 912 $a991002014059707536 945 $aLE002 Sal. I L 1$g1$i2002000738820$lle002$o-$pE0.00$q-$rn$so $t0$u0$v0$w0$x0$y.i10359758$z27-06-02 945 $aLE009 STOR.30-27$g1$i2009000085992$lle009$o-$pE0.00$q-$rn$so $t0$u0$v0$w0$x0$y.i12536799$z24-06-03 996 $aBrindisi turistica$9201800 997 $aUNISALENTO 998 $ale002$ale009$b01-01-01$cm$da $e-$fita$git $h0$i1 LEADER 01540nam 2200385 a 450 001 9910700904803321 005 20110921092521.0 035 $a(CKB)5470000002413984 035 $a(OCoLC)753932072 035 $a(EXLCZ)995470000002413984 100 $a20110921d2011 ua 0 101 0 $aeng 135 $aurmn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSocial security statements$b[electronic resource] $eobservations on SSA's plans for the social security statement : testimony before the Subcommittee on Social Security, Committee on Ways and Means, House of Representatives /$fstatement of Barbara D. Bovbjerg 210 1$a[Washington, D.C.] :$cU.S. Govt. Accountability Office,$d[2011] 215 $a1 online resource (21 pages) $ccolor illustrations 225 1 $aTestimony ;$vGAO-11-787T 300 $aTitle from PDF title screen (viewed Aug. 24, 2011). 300 $a"For release ... July 8, 2011." 320 $aIncludes bibliographical references. 517 $aSocial security statements 606 $aSocial security$zUnited States 615 0$aSocial security 700 $aBovbjerg$b Barbara D$01380758 712 02$aUnited States.$bCongress.$bHouse.$bCommittee on Ways and Means.$bSubcommittee on Social Security. 712 02$aUnited States.$bGovernment Accountability Office. 801 0$bGPO 801 1$bGPO 906 $aBOOK 912 $a9910700904803321 996 $aSocial security statements$93448399 997 $aUNINA LEADER 09857nam 22006853 450 001 9910877543003321 005 20251114221257.0 010 $a9781523155095 010 $a1523155094 010 $a9781119626824 010 $a111962682X 010 $a9781119626879 010 $a1119626870 010 $a9781119626718 010 $a1119626714 035 $a(CKB)4100000010858970 035 $a(MiAaPQ)EBC6154238 035 $a(Au-PeEL)EBL6154238 035 $a(CaSebORM)9781119626800 035 $a(OCoLC)1128890321 035 $a(Perlego)1433138 035 $a(EXLCZ)994100000010858970 100 $a20210901d2020 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplied Numerical Methods Using MATLAB 205 $a2nd ed. 210 1$aNewark :$cJohn Wiley & Sons, Incorporated,$d2020. 210 4$d©2020. 215 $a1 online resource (653 pages) 311 08$a9781119626800 311 08$a1119626803 327 $aCover -- Title Page -- Copyright -- Contents -- Preface -- Acknowledgments -- About the Companion Website -- Chapter 1 MATLAB Usage and Computational Errors -- 1.1 Basic Operations of MATLAB -- 1.1.1 Input/Output of Data from MATLAB Command Window -- 1.1.2 Input/Output of Data Through Files -- 1.1.3 Input/Output of Data Using Keyboard -- 1.1.4 Two?Dimensional (2D) Graphic Input/Output -- 1.1.5 Three Dimensional (3D) Graphic Output -- 1.1.6 Mathematical Functions -- 1.1.7 Operations on Vectors and Matrices -- 1.1.8 Random Number Generators -- 1.1.9 Flow Control -- 1.2 Computer Errors vs. Human Mistakes -- 1.2.1 IEEE 64?bit Floating?Point Number Representation -- 1.2.2 Various Kinds of Computing Errors -- 1.2.3 Absolute/Relative Computing Errors -- 1.2.4 Error Propagation -- 1.2.5 Tips for Avoiding Large Errors -- 1.3 Toward Good Program -- 1.3.1 Nested Computing for Computational Efficiency -- 1.3.2 Vector Operation vs. Loop Iteration -- 1.3.3 Iterative Routine vs. Recursive Routine -- 1.3.4 To Avoid Runtime Error -- 1.3.5 Parameter Sharing via GLOBAL Variables -- 1.3.6 Parameter Passing Through VARARGIN -- 1.3.7 Adaptive Input Argument List -- Chapter 2 System of Linear Equations -- 2.1 Solution for a System of Linear Equations -- 2.1.1 The Nonsingular Case (M & -- equals -- N) -- 2.1.2 The Underdetermined Case (M < -- N): Minimum?norm Solution -- 2.1.3 The Overdetermined Case (M > -- N): Least?squares Error Solution -- 2.1.4 Recursive Least?Squares Estimation (RLSE) -- 2.2 Solving a System of Linear Equations -- 2.2.1 Gauss(ian) Elimination -- 2.2.2 Partial Pivoting -- 2.2.3 Gauss?Jordan Elimination -- 2.3 Inverse Matrix -- 2.4 Decomposition (Factorization) -- 2.4.1 LU Decomposition (Factorization) - Triangularization -- 2.4.2 Other Decomposition (Factorization) - Cholesky, QR and SVD -- 2.5 Iterative Methods to Solve Equations. 327 $a2.5.1 Jacobi Iteration -- 2.5.2 Gauss?Seidel Iteration -- 2.5.3 The Convergence of Jacobi and Gauss?Seidel Iterations -- Chapter 3 Interpolation and Curve Fitting -- 3.1 Interpolation by Lagrange Polynomial -- 3.2 Interpolation by Newton Polynomial -- 3.3 Approximation by Chebyshev Polynomial -- 3.4 Pade Approximation by Rational Function -- 3.5 Interpolation by Cubic Spline -- 3.6 Hermite Interpolating Polynomial -- 3.7 Two?Dimensional Interpolation -- 3.8 Curve Fitting -- 3.8.1 Straight?Line Fit - A Polynomial Function of Degree 1 -- 3.8.2 Polynomial Curve Fit - A Polynomial Function of Higher Degree -- 3.8.3 Exponential Curve Fit and Other Functions -- 3.9 Fourier Transform -- 3.9.1 FFT vs. DFT -- 3.9.2 Physical Meaning of DFT -- 3.9.3 Interpolation by Using DFS -- Chapter 4 Nonlinear Equations -- 4.1 Iterative Method toward Fixed Point -- 4.2 Bisection Method -- 4.3 False Position or Regula Falsi Method -- 4.4 Newton(?Raphson) Method -- 4.5 Secant Method -- 4.6 Newton Method for a System of Nonlinear Equations -- 4.7 Bairstow's Method for a Polynomial Equation -- 4.8 Symbolic Solution for Equations -- 4.9 Real?World Problems -- Chapter 5 Numerical Differentiation/Integration -- 5.1 Difference Approximation for the First Derivative -- 5.2 Approximation Error of the First Derivative -- 5.3 Difference Approximation for Second and Higher Derivative -- 5.4 Interpolating Polynomial and Numerical Differential -- 5.5 Numerical Integration and Quadrature -- 5.6 Trapezoidal Method and Simpson Method -- 5.7 Recursive Rule and Romberg Integration -- 5.8 Adaptive Quadrature -- 5.9 Gauss Quadrature -- 5.9.1 Gauss?Legendre Integration -- 5.9.2 Gauss?Hermite Integration -- 5.9.3 Gauss?Laguerre Integration -- 5.9.4 Gauss?Chebyshev Integration -- 5.10 Double Integral -- 5.11 Integration Involving PWL Function -- Chapter 6 Ordinary Differential Equations. 327 $a6.1 Euler's Method -- 6.2 Heun's Method - Trapezoidal Method -- 6.3 Runge?Kutta Method -- 6.4 Predictor?Corrector Method -- 6.4.1 Adams?Bashforth?Moulton Method -- 6.4.2 Hamming Method -- 6.4.3 Comparison of Methods -- 6.5 Vector Differential Equations -- 6.5.1 State Equation -- 6.5.2 Discretization of LTI State Equation -- 6.5.3 High?order Differential Equation to State Equation -- 6.5.4 Stiff Equation -- 6.6 Boundary Value Problem (BVP) -- 6.6.1 Shooting Method -- 6.6.2 Finite Difference Method -- Chapter 7 Optimization -- 7.1 Unconstrained Optimization -- 7.1.1 Golden Search Method -- 7.1.2 Quadratic Approximation Method -- 7.1.3 Nelder?Mead Method -- 7.1.4 Steepest Descent Method -- 7.1.5 Newton Method -- 7.1.6 Conjugate Gradient Method -- 7.1.7 Simulated Annealing -- 7.1.8 Genetic Algorithm -- 7.2 Constrained Optimization -- 7.2.1 Lagrange Multiplier Method -- 7.2.2 Penalty Function Method -- 7.3 MATLAB Built?In Functions for Optimization -- 7.3.1 Unconstrained Optimization -- 7.3.2 Constrained Optimization -- 7.3.3 Linear Programming (LP) -- 7.3.4 Mixed Integer Linear Programming (MILP) -- 7.4 Neural Network[K?1] -- 7.5 Adaptive Filter[Y?3] -- 7.6 Recursive Least Square Estimation (RLSE)[Y?3] -- Chapter 8 Matrices and Eigenvalues -- 8.1 Eigenvalues and Eigenvectors -- 8.2 Similarity Transformation and Diagonalization -- 8.3 Power Method -- 8.3.1 Scaled Power Method -- 8.3.2 Inverse Power Method -- 8.3.3 Shifted Inverse Power Method -- 8.4 Jacobi Method -- 8.5 Gram?Schmidt Orthonormalization and QR Decomposition -- 8.6 Physical Meaning of Eigenvalues/Eigenvectors -- 8.7 Differential Equations with Eigenvectors -- 8.8 DoA Estimation with Eigenvectors[Y-3] -- Chapter 9 Partial Differential Equations -- 9.1 Elliptic PDE -- 9.2 Parabolic PDE -- 9.2.1 The Explicit Forward Euler Method -- 9.2.2 The Implicit Backward Euler Method. 327 $a9.2.3 The Crank?Nicholson Method -- 9.2.4 Using the MATLAB function 'pdepe()' -- 9.2.5 Two?Dimensional Parabolic PDEs -- 9.3 Hyperbolic PDES -- 9.3.1 The Explicit Central Difference Method -- 9.3.2 Two?Dimensional Hyperbolic PDEs -- 9.4 Finite Element Method (FEM) for Solving PDE -- 9.5 GUI of MATLAB for Solving PDES - PDEtool -- 9.5.1 Basic PDEs Solvable by PDEtool -- 9.5.2 The Usage of PDEtool -- 9.5.3 Examples of Using PDEtool to Solve PDEs -- Appendix A Mean Value Theorem -- Appendix B Matrix Operations/Properties -- B.1 Addition and Subtraction -- B.2 Multiplication -- B.3 Determinant -- B.4 Eigenvalues and Eigenvectors of a Matrix1 -- B.5 Inverse Matrix -- B.6 Symmetric/Hermitian Matrix -- B.7 Orthogonal/Unitary Matrix -- B.8 Permutation Matrix -- B.9 Rank -- B.10 Row Space and Null Space -- B.11 Row Echelon Form -- B.12 Positive Definiteness -- B.13 Scalar (Dot) Product and Vector (Cross) Product -- B.14 Matrix Inversion Lemma -- Appendix C Differentiation W.R.T. A Vector -- Appendix D Laplace Transform -- Appendix E Fourier Transform -- Appendix F Useful Formulas -- Appendix G Symbolic Computation -- G.1 How to Declare Symbolic Variables and Handle Symbolic Expressions -- G.2 Calculus -- G.2.1 Symbolic Summation -- G.2.2 Limits -- G.2.3 Differentiation -- G.2.4 Integration -- G.2.5 Taylor Series Expansion -- G.3 Linear Algebra -- G.4 Solving Algebraic Equations -- G.5 Solving Differential Equations -- Appendix H Sparse Matrices -- Appendix I MATLAB -- References -- Index -- Index for MATLAB Functions -- Index for Tables -- EULA. 330 $a"This book makes use of MATLAB software to teach the fundamental concepts using the software to solve practical engineering and/or science problems. The programs are presented in a complete form so that readers can run them instantly with no programming skill, allowing them to focus on understanding the mathematical manipulation process and making interpretations of the results. The book targets students who do not like and/or do not have time to derive and prove mathematical results, helping them develop their problem-solving capability without being involved in details about the MATLAB codes. It also targets students who want to delve into details, helping them understand underlying algorithms and equations as deeply as they want"--$cProvided by publisher. 606 $aNumerical analysis$xData processing 615 0$aNumerical analysis$xData processing. 676 $a518 700 $aYang$b Wo?n-yo?ng$f1953-$0893540 701 $aCao$b Wenwu$01751212 701 $aKim$b Jaekwon$01751213 701 $aPark$b Kyung W$030169 701 $aPark$b Ho-Hyun$01751214 701 $aJoung$b Jingon$01751215 701 $aRo$b Jong-Suk$01751216 701 $aLee$b Han L$01751217 701 $aHong$b Cheol-Ho$01751218 701 $aIm$b Taeho$01751219 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910877543003321 996 $aApplied Numerical Methods Using MATLAB$94456057 997 $aUNINA