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==Topics List== | ==Topics List== | ||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
− | ! Date !! Sections !! Topics !! Prerequisite Skills !! Student Learning Outcomes | + | ! Date !! Sections [Sauer 3rd ed] !! Topics !! Prerequisite Skills !! Student Learning Outcomes |
|- | |- | ||
− | |Week 1 | + | | Week.1 |
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− | + | 0.2 and 1.1 | |
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− | * | + | * Loss of significant digits |
− | * | + | * Bisection Method |
+ | * Brief introduction to matlab | ||
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− | * | + | * binary number system; |
− | * | + | * Taylor's theorem; |
+ | * intermediate value theorem | ||
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− | * Nested | + | * Nested multiplication for evaluating polynomials |
− | * Machine | + | * Machine representation of real numbers |
− | * Loss of | + | * Loss of significant digits in numerical computing |
* Review of Taylor's Theorem | * Review of Taylor's Theorem | ||
− | + | * Bisection method and implementation | |
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|- | |- | ||
− | |Week | + | | Week.2 |
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− | + | 1.2 and 1.3 | |
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* Fixed-Point Iteration | * Fixed-Point Iteration | ||
+ | * Limits of Accuracy: Conditioning of problems | ||
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− | * | + | * limit of sequences |
− | * | + | * multiplicity of solution of equations. |
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− | * | + | * Geometric interpretation |
− | + | * Convergence of fixed point iterations | |
− | * | + | * Order of convergence of iterative methods |
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− | * | + | * Wilkinson polynomial and other examples |
− | + | * Sensitivity analysis of root-finding | |
− | * | + | * Error magnification factor for solution of equations |
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− | * Error | ||
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|- | |- | ||
− | |Week 3 | + | | Week.3 |
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− | + | 1.4 and 1.5 | |
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− | * | + | * Newton's Method |
+ | * Root-Finding without Derivatives | ||
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− | * Remainder of Taylor's | + | * Remainder of Taylor's series |
− | * | + | * intermediate value theorem. |
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− | * Algebraic and | + | * Algebraic and geometric interpretation of Newton's method |
− | * Error | + | * Error analysis for Newton's method based on Taylor's theorem |
− | * Newton's | + | * Newton's method as a fixed point iteration |
− | * Modified Newton's Method and its | + | * Modified Newton's method and its rate of convergence |
+ | |||
+ | * Secant Method and its convergence, | ||
+ | * Method of False Position, Muller's Method: | ||
+ | * Stopping criteria for iterative methods | ||
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− | |Week | + | | Week.4 |
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− | + | 2.1 and 2.2 | |
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− | * | + | * Solve Systems of Linear Equations: Gaussian Elmination |
+ | * Solve System of Linear Equations: LU Decomposition | ||
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− | * | + | * Matrix-matrix products and matrix-vector products |
− | * | + | * inverse matrix |
− | * | + | * elementary row operations |
+ | * product and inverse of matrices for elementary row operations. | ||
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− | * | + | * Gaussian elimination and its operation counts |
− | * | + | * Gaussian elimination with pivoting |
− | * | + | * Implementation of Gauss elimination |
− | * | + | |
+ | * Matrices for elementary row operations | ||
+ | * Gauss elimination as matrix products | ||
+ | * Advantages of solutions by LU decomposition | ||
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|- | |- | ||
− | |Week | + | | Week.5 |
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− | + | 2.3 and 2.4 | |
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* Error Analysis for Solution of Ax=b | * Error Analysis for Solution of Ax=b | ||
− | * | + | * Iterative Methods for Solving Ax=b |
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− | * | + | * Length of vectors |
+ | * eigenvalue and eigenvectors of matrix | ||
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− | * | + | * various norms for vectors and matrices: compatibility of vector and matrix norms. |
− | + | * Error Analysis for the solution of Ax=b | |
− | + | * Error magnification factor and condition number of matrix | |
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− | + | * Jacobi method, Gauss-Seidel method, Successive-Over-Relaxation (SOR) method | |
− | + | * Convergence of Jacobi Method, GS method and SOR method. | |
− | + | * spectral radius of matrix | |
− | * Error Analysis for | + | * convergence of general iterative method for solving system of linear equations, |
− | * Error | + | * Sparse Matrix |
− | + | * Comparison of Gauss Elimination and iterative methods | |
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− | * Comparison of Gauss Elimination and | ||
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|- | |- | ||
− | |Week | + | | Week.6 |
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− | + | 2.6 and 2.7 | |
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− | * | + | * Conjugate Gradient Method |
+ | * Nonlinear System of Equations | ||
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− | * | + | * scalar product of vectors |
− | * | + | * determinant and eigenvalues of matrix |
− | * | + | * quadratic polynomials of n-variables |
+ | * partial derivatives and gradients | ||
+ | * chain rule for partial derivatives. | ||
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− | + | * Symmetric positive definite matrix and properties | |
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− | * Symmetric | ||
* Construction of Conjugate Gradient (CG) Method | * Construction of Conjugate Gradient (CG) Method | ||
− | * | + | * Propertise of CG Method |
− | * Preconditioning for CG Method | + | * Preconditioning for CG method |
+ | |||
+ | * Taylor's Theorem for multi-variate vector valued functions: | ||
+ | * Newton's Method: | ||
+ | * Broyden's Method | ||
+ | |||
|- | |- | ||
− | |Week | + | | Week.7 |
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− | + | 3.1 and 3.2 | |
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− | * | + | * Data and Interpolating Functions |
+ | * Interpolation Error and Runge Phenomenon | ||
+ | * Chebyshev interpolation | ||
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− | * | + | * Fundamental theorem of algebra |
− | * | + | * Rolle's theorem. |
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− | * | + | * Lagrange Basis Functions: |
− | * | + | * Properties of Lagrange basis functions: |
− | * Properties of | + | * Lagrange form of the interpolation polynomials |
− | * | + | |
+ | * Newton's Divided Differences: | ||
+ | * Properties of Newton's divided differences: | ||
+ | * Newton's Form of the interpolation polynomials | ||
+ | |||
+ | * Interpolation error analysis | ||
+ | * Runge phenomenon | ||
+ | |||
+ | * Chebyshev Polynomial | ||
+ | * Error estimates for Chebyshev interpolation | ||
+ | |||
+ | |||
|- | |- | ||
− | |Week | + | | Week.8 |
|| | || | ||
− | + | 3.4, 3.5 and 4.1 | |
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− | * | + | * Cubic Splines |
+ | * Bezier Curves | ||
+ | * Least Square Method | ||
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− | * | + | * one-sided limits |
− | * | + | * continuity of functions |
− | * | + | * indefinite integrals |
− | * | + | * extremum values of multivariate quadratic functions. |
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− | * | + | * Cubic splines |
− | + | * construction of cubic splines for interpolation | |
− | + | * end conditions | |
− | + | * properties of cubic spline interpolation | |
− | + | ||
− | + | * Bezier Curve and fonts | |
− | + | ||
− | + | * Least square method for solving inconsistent system of linear equations. | |
− | + | * Basic properties of least square solutions: | |
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− | * Bezier Curve and | ||
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− | |Week 9 | + | | Week.9 |
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− | + | 4.2 and 4.5 | |
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− | * | + | * Mathematical Models and Data Fitting |
+ | * Nonlinear Least Square Fitting | ||
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− | * | + | * linear spaces, basis functions |
− | * | + | * product rule and chain rule for vector valued multivariate functions. |
− | |||
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− | * Least square method for curve fitting and statistical modeling | + | * Least square method for curve fitting and statistical modeling. |
* Survey of Models: linear model, periodic model, exponential models, logistic model, etc | * Survey of Models: linear model, periodic model, exponential models, logistic model, etc | ||
+ | |||
+ | * Taylor's theorem for vector valued multivariate functions. | ||
+ | * Gauss-Newton Method | ||
+ | * Levenberg-Marquardt Method | ||
+ | |||
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|- | |- | ||
− | |Week | + | | Week.10 |
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− | + | 5.1, 5.2 and 5.3 | |
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− | * | + | * Numerical Differentiation |
+ | * Numerical Integration: Newton-Cotes Formulas | ||
+ | * Numerical Integration: Romberg's Technique | ||
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− | * | + | * Taylor's theorem |
− | * | + | * interpolation error estimates |
− | * | + | * properties of definite inetgrals |
− | |||
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− | * | + | * Finite difference (FD) approximations of 1st order derivative and their error analysis |
− | * | + | * FD approximations of 2nd order derivatives and their error analysis |
+ | * Undetermined coefficient method for FD approximation | ||
+ | * Extropolation technique for improving the order of approximation | ||
+ | |||
+ | * Midpoint rule, trapezoid rule and Simpson's rule; | ||
+ | * Error analysis based on Taylor's Theorem and interpolation errors | ||
+ | * Degree of precision of quadrature rules | ||
+ | * Composite quadrature rules | ||
+ | |||
+ | * Motivation, construction and implementation of Romberg's technique. | ||
+ | |||
+ | |||
|- | |- | ||
− | |Week | + | | Week.11 |
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− | + | 5.4 and 5.5 | |
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− | * | + | * Adaptive Numerical Integration |
+ | * Gauss Quadrature Formulas | ||
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− | * | + | * long divisions |
− | * | + | * changing variables for definite integrals |
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− | + | * How to estimate the error on a subinterval | |
− | + | * How to mark subintervals to be further refinement? | |
− | + | * Implementation of adaptive numerical integration techniques. | |
− | + | ||
− | + | * Motivation and difficulties with straightforward approach. | |
− | + | * Orthogonal polynomials, | |
− | + | * Legendre polynomials and their basic properties; | |
− | + | * Gauss quadrature rule based on Legendre polynomials | |
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− | * How to estimate the error on a | ||
− | * How to mark | ||
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− | * Motivation and difficulties with straightforward approach | ||
− | * Legendre polynomials and their basic properties | ||
− | * Gauss | ||
* Degree of precision of Gauss Quadrature | * Degree of precision of Gauss Quadrature | ||
* Gauss quadrature formula on general interval and composite Gauss rules | * Gauss quadrature formula on general interval and composite Gauss rules | ||
+ | |||
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|- | |- | ||
− | |Week | + | | Week.12 |
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− | + | 10.1 and 11.1 | |
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− | * | + | * Discrete Fourier Transform and FFT |
+ | * Discrete Cosine Transform (optional) | ||
+ | * Image Compression (optional) | ||
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− | * | + | * complex numbers and complex variables |
− | * | + | * integration by parts |
+ | * convergence of sequences and series. | ||
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− | * | + | * Fourier Series, |
− | * | + | * Discrete Fourier Transform |
− | * | + | * Matrix Form of Discrete Fourier Transform: |
− | * | + | * Inverse Discrete Fourier Transform: |
− | * | + | * DFT and Trigonometric interpolation |
+ | * Algorithm for computing DFT: Fast Fourier Transform (FFT) | ||
+ | |||
+ | * Discrete Cosine Transform (DCT), | ||
+ | * DCT and Interpolation by Cosine Functions | ||
+ | * Relation between DFT and DCT: | ||
+ | * Fourier Transform of 2-Dimensional Functions | ||
+ | * DCT of 2-Dimensional Functions: | ||
+ | * Interpolation Theorem for 2-Dimensional DCT | ||
+ | |||
+ | * Digital Gray scale images and color color images: | ||
+ | * RGB format: | ||
+ | * YCbCr (or YUV) format: | ||
+ | * Convertion between RGB and YUV formats: | ||
+ | * Quantization, Image Compression and Decompression | ||
+ | |||
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|- | |- | ||
− | |Week | + | | Week.13 |
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− | + | 12.1 and 12.2 | |
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− | * | + | * Power Iteration Methods |
+ | * QR Algorithm for Computing Eigenvalues | ||
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− | * | + | * properties of eigen values and eigenvectors |
− | * | + | * Gram-Schmidt orthogonalization |
|| | || | ||
− | * | + | * Power iteration and its rate of convergence. |
− | * | + | * Inverse Power Iteration, |
− | * | + | * Inverse Power Iteration with Shift |
− | * | + | * Rayleigh Quotient Iteration |
− | * | + | |
+ | |||
+ | * Definition and basic properties of orthogonal matrices: | ||
+ | * QR-Factorization based on Gram-Schmidt Orthogonalization: | ||
+ | * Normalized Simultaneous Iteration (NSI). | ||
+ | * Unshifted QR Algorithm: | ||
+ | * Shifted QR Algorithm: | ||
+ | |||
+ | |||
+ | |||
|- | |- | ||
− | |Week | + | | Week.14 |
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− | + | 12.2 | |
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− | * | + | * Algorithm for Computing Eigenvalues: Speed up of QR-algorithm: |
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− | * | + | * matrices for orthogonal projection and reflection |
− | + | * block matrices and their products | |
− | + | * similar matrices. | |
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+ | * Upper Hessenberg form (UHF) | ||
+ | * Householder Reflector | ||
* Convert a matrix into UHF by Householder reflectors | * Convert a matrix into UHF by Householder reflectors | ||
+ | |||
|} | |} |
Latest revision as of 14:38, 17 August 2020
Course Catalog
MAT 3633. Numerical Analysis. (3-0) 3 Credit Hours.
Prerequisites: MAT2233, MAT3213, and one of the following: CS1063, CS1714, or CS2073. Solution of linear and nonlinear equations, curve-fitting, and eigenvalue problems. Generally offered: Fall, Spring. Differential Tuition: $150.
Topics List
Date | Sections [Sauer 3rd ed] | Topics | Prerequisite Skills | Student Learning Outcomes | |
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Week.1 |
0.2 and 1.1 |
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Week.2 |
1.2 and 1.3 |
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Week.3 |
1.4 and 1.5 |
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Week.4 |
2.1 and 2.2 |
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Week.5 |
2.3 and 2.4 |
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Week.6 |
2.6 and 2.7 |
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Week.7 |
3.1 and 3.2 |
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Week.8 |
3.4, 3.5 and 4.1 |
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Week.9 |
4.2 and 4.5 |
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Week.10 |
5.1, 5.2 and 5.3 |
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Week.11 |
5.4 and 5.5 |
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Week.12 |
10.1 and 11.1 |
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Week.13 |
12.1 and 12.2 |
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Week.14 |
12.2 |
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