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Applied Numerical Methods Using MATLAB
| Applied Numerical Methods Using MATLAB |
| Autore | Yang Won Y |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2020 |
| Descrizione fisica | 1 online resource (653 pages) |
| Altri autori (Persone) |
CaoWenwu
KimJaekwon ParkKyung W ParkHo-Hyun JoungJingon RoJong-Suk LeeHan L HongCheol-Ho ImTaeho |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-119-62682-X
1-119-62687-0 1-119-62671-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- 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.
2.5.1 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. 6.1 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. 9.2.3 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. |
| Record Nr. | UNINA-9910554877803321 |
Yang Won Y
|
||
| Newark : , : John Wiley & Sons, Incorporated, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applied Numerical Methods Using MATLAB
| Applied Numerical Methods Using MATLAB |
| Autore | Yang Won Y |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2020 |
| Descrizione fisica | 1 online resource (653 pages) |
| Disciplina | 518 |
| Altri autori (Persone) |
CaoWenwu
KimJaekwon ParkKyung W ParkHo-Hyun JoungJingon RoJong-Suk LeeHan L HongCheol-Ho ImTaeho |
| Soggetto topico | Numerical analysis - Data processing |
| ISBN |
1-5231-5509-4
1-119-62682-X 1-119-62687-0 1-119-62671-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- 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.
2.5.1 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. 6.1 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. 9.2.3 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. |
| Record Nr. | UNINA-9910830712603321 |
|
Yang Won Y
|
||
| Newark : , : John Wiley & Sons, Incorporated, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applied Numerical Methods Using MATLAB
| Applied Numerical Methods Using MATLAB |
| Autore | Yang Won Y |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2020 |
| Descrizione fisica | 1 online resource (653 pages) |
| Disciplina | 518 |
| Altri autori (Persone) |
CaoWenwu
KimJaekwon ParkKyung W ParkHo-Hyun JoungJingon RoJong-Suk LeeHan L HongCheol-Ho ImTaeho |
| Soggetto topico | Numerical analysis - Data processing |
| ISBN |
1-5231-5509-4
1-119-62682-X 1-119-62687-0 1-119-62671-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- 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.
2.5.1 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. 6.1 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. 9.2.3 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. |
| Record Nr. | UNINA-9910841170603321 |
|
Yang Won Y
|
||
| Newark : , : John Wiley & Sons, Incorporated, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Electronic circuits with MATLAB, PSpice, and Smith Chart / / Won Y. Yang [and nine others]
| Electronic circuits with MATLAB, PSpice, and Smith Chart / / Won Y. Yang [and nine others] |
| Autore | Yang Wŏn-yŏng <1953-> |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, NJ : , : Wiley, , [2020] |
| Descrizione fisica | 1 online resource (863 pages) |
| Disciplina | 621.3815 |
| Soggetto topico | Electronic circuit design - Data processing |
| ISBN |
1-5231-3297-3
1-119-59896-6 1-119-59897-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910555126003321 |
|
Yang Wŏn-yŏng <1953->
|
||
| Hoboken, NJ : , : Wiley, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Electronic circuits with MATLAB, PSpice, and Smith Chart / / Won Y. Yang [and nine others]
| Electronic circuits with MATLAB, PSpice, and Smith Chart / / Won Y. Yang [and nine others] |
| Autore | Yang Wŏn-yŏng <1953-> |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, NJ : , : Wiley, , [2020] |
| Descrizione fisica | 1 online resource (863 pages) |
| Disciplina | 621.3815 |
| Soggetto topico | Electronic circuit design - Data processing |
| ISBN |
1-5231-3297-3
1-119-59896-6 1-119-59897-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910810678303321 |
|
Yang Wŏn-yŏng <1953->
|
||
| Hoboken, NJ : , : Wiley, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||