| 1. |
 |
1-1. Introduction: Overview |
Introduction to numerical analysis |
 |
|
|
1-2. Introduction: Basic MATLAB Tutorial (1) |
MATLAB fundamental operation |
|
| 2. |
|
1-3. Introduction: Basic MATLAB Tutorial (2) |
MATLAB Matrix operations and data presentation |
|
|
|
2-1. Error Analysis: Error in Numerical Methods |
Definition and types of error |
|
|
|
2-2. Error Analysis: Taylor Series |
Taylor series and truncation error |
|
| 3. |
|
3-1. Root-Finding Methods: Overview |
Steps for solving one-variable problems |
|
|
|
3-2. Root-Finding Methods: Closed Method (1) |
Bisection method |
|
|
|
3-3. Root-Finding Methods: Closed Method (2) |
False position method |
|
| 4. |
|
3-4. Root-Finding Methods: Open Method (1) |
Secant method |
|
|
|
3-5. Root-Finding Methods: Open Method (2) |
Newton-Raphson method |
|
|
|
3-6. Root-Finding Methods: Open Method (3) |
Fixed-point iteration method |
|
| 5. |
|
4-1. Linear Systems: Overview |
Matrix representation of linear systems |
|
|
|
4-2. Linear Systems: Gaussian Elimination |
Gaussian elimination |
|
|
|
4-3. Linear Systems: LU Decomposition (1) |
Doolittle method for LU decomposition |
|
| 6. |
|
4-4. Linear Systems: LU Decomposition (2) |
Crout method for LU decomposition |
|
|
|
4-5. Linear Systems: LU Decomposition (3) |
Tutorial for LU decomposition |
|
|
|
4-6. Linear Systems: Jacobi Method |
Jacobi method and matrix norm |
|
| 7. |
|
4-7. Linear Systems: Gauss-Seidel Method (1) |
Gauss-Seidel method and relaxation methods |
|
|
|
4-8. Linear Systems: Gauss-Seidel Method (2) |
Tutorial for Gauss-Seidel method and relaxation methods |
|
|
|
5-1. Optimization: Fundamental Concepts and Algorithms |
Concepts in optimization and optimization algorithms |
|
| 8. |
|
5-2. Optimization: Golden Section Search and Newton s Method |
Tutorial on the golden section search and Newton's method |
|
|
|
6-1. Curve Fitting: Interpolation (1) |
Concepts in curve fitting and linear interpolation |
|
|
|
6-2. Curve Fitting: Interpolation (2) |
Polynomial and spline interpolation |
|
| 9. |
|
6-3. Curve Fitting: Regression |
Regression methods and least squares regression |
|
|
|
7-1. Differentiation and Integration: Numerical Differentiation (1) |
Forward, backward and central difference methods |
|
|
|
7-2. Differentiation and Integration: Numerical Differentiation (2) |
Tutorial for numerical differentiation |
|
| 10. |
|
7-3. Differentiation and Integration: Numerical Integration (1) |
Newton–Cotes methods: midpoint and trapezoidal rules |
|
|
|
7-4. Differentiation and Integration: Numerical Integration (2) |
Newton–Cotes methods: Simpson’s rule |
|
|
|
7-5. Differentiation and Integration: Numerical Integration (3) |
Monte Carlo methods |
|
| 11. |
|
8-1. Ordinary Differential Equations: Overview |
Numerical methods for solving initial value problems |
|
|
|
8-2. Ordinary Differential Equations: Euler Method |
Forward Euler method |
|
|
|
8-3. Ordinary Differential Equations: Heun s Method |
Heun's method and Butcher's tableau |
|
| 12. |
|
8-4. Ordinary Differential Equations: Runge-Kutta Method (1) |
Second-order Runge-Kutta method |
|
|
|
8-5. Ordinary Differential Equations: Runge-Kutta Method (2) |
Fourth-order Runge-Kutta method |
|
|
|
9-1. Machine Learning Basics: Overview |
Fundamental concepts of machine learning |
|
| 13. |
|
9-2. Machine Learning Basics: Supervised Learning |
Supervised learning and support vector machines |
|
|
|
9-3. Machine Learning Basics: Unsupervised Learning |
Unsupervised learning and k-means clustering |
|
|
|
10. Course Review |
Review of fundamental numerical analysis |
|
|
 |
NA_Chapter1_Introduction |
강의 교안 |
 |
|
|
NA_Chapter2_Error_Analysis |
강의 교안 |
|
|
|
NA_Chapter3_Root_Finding_Methods |
강의 교안 |
|
|
|
NA_Chapter4_Linear_Systems |
강의 교안 |
|
|
|
NA_Chapter5_Optimization |
강의 교안 |
|
|
|
NA_Chapter6_Curve_Fitting |
강의 교안 |
|
|
|
NA_Chapter7_Differentiation_and_Integration |
강의 교안 |
|
|
|
NA_Chapter8_Ordinary_Differential_Equations |
강의 교안 |
|
|
|
NA_Chapter9_Machine_Learning_Basics |
강의 교안 |
|
페이스북
트위터
카카오톡
네이버밴드
링크복사
