바로가기

모두를 위한 열린 강좌 KOCW

주메뉴

강의사진
  • 주제분류
    공학 >전기ㆍ전자 >전자공학
  • 강의학기
    2013년 2학기
  • 조회수
    11,188
  •  
This course is intended to undergraduate students where we study several numerical techniques and their implementation using matlab program. The practical aspects of systems are analyzed under imperfect conditions
math and numerical models
배속
  • 이전차시
  • 다음차시

차시별 강의

PDF VIDEO SWF AUDIO DOC AX
1. 비디오 math and numerical models In this lecture, we introduce for numerical analysis by comparing between analytical and numerical models URL
비디오 matlab (handling scalar variables) Introduction to matlab environment and handling scalar variables and several basic operations on them URL
2. 비디오 matlab (handling vector variables) handling vector variables in matlab and several basic operations on them including functions and plotting URL
3. 비디오 matlab (handling matrices variables) handling vector variables in matlab and several basic operations on them including functions and plotting URL
4. 비디오 programming with matlab introduction to more advanced topic in matlab such as plotting, inline functions, handling complex equations etc. URL
5. 비디오 Roundoff and Truncation Errors : Matlab hints analyze sources of errors in computations with focus on reducing the errors URL
비디오 Roots: Bracketing methods : Introduction & Bracketing methods introducing bracketing methods for finding the intervals of roots URL
비디오 Roots: Bracketing methods : open methods & matlab hints introducing open methods for finding the intervals of roots URL
비디오 Linear algebraic equations : Introduction to matrices introduce simple linear systems and several special matrices and their use URL
비디오 Linear algebraic equations : matrices operaions Introduce several simple matrix-matrix and matrix-vector operations URL
비디오 Linear algebraic equations : singular value decomposition Shed light o singular valus and their use in analyzing the stability of systems URL
7. 비디오 Gauss elimination: Cramer's rule & Naive Gauss elimination Introduce Cramer's rule and Gausse elimiation as methods to solve linear algebraic systems URL
비디오 LU decomposition and Cholesky decomposition: Gauss elimination Introduce LU and Cholesky decompositoon methods and introdce for matrix inversion URL
8. 비디오 Matrix inversion using LU decomposition Due to its low complexity and stability, LU is used as a matrix inversion technique URL
비디오 Error analysis and system condition In presence of noise, the system performance is analyzed using already studied algorithms including matrix inversion. Also, the idea and implementation of the maximum likelihood are investigated URL
9. 비디오 Iterative method - Gauss-seidel method introduce iterative methods to solve linear systems - Gauss-Seidel method URL
비디오 Iterative method - newton-raphson method introduce nonlinear systems and introduce the newton-raphson method URL
비디오 Introduce EVD & SVD Introduction to singular value decomposition and eigen value decomposition URL
비디오 EVD (eigen value decompositon) Introduce the characteristic polynomial and how to obtain the eigen values and relation with trace and det of a matrix URL
비디오 Power method Introduce the power method to numerically obtain the minimum eigenvalue of a matrix URL
비디오 EVD vs. SVD introduce points of similarity and difference between eigenvalues and singular values URL
10. 비디오 Introduction & overview introduce curve fitting URL
비디오 Liner least-squares regression introduce the linear least squares regression and the derivation of the line parameters URL
비디오 Linearization of nonliner models linearization of power, exponential and saturation rate nonlinear models URL
비디오 Practice explanation A practice on the linear curve fitting and the linearization of nonlinear models URL
11. 비디오 introduction (and reply to twitter questions) more examples of linear curve fitting and linearization of nonlinear models URL
비디오 polynomial regression - single variable introduce the polynomial regression (nonlinearregression) and the derivation of the polynomial parameters URL
비디오 polynomial regression - 2 variables apply the nonlinear regression to the case of two independent variables URL
12. 비디오 Introduction (~ slide 6) Introduction to interpolation URL
비디오 Newton interpolation polynomial introduce the newton interpolation polynomial and discuss accuracy of this method URL
비디오 Lagrange interpolation polynomial introduce the lagrange interpolation polynomial and discuss accuracy of this method URL
비디오 Extrapolation introduce the idea behind extrapolation and the danger of this technique specially when using high order polynomials URL
13. 비디오 Integration and Newton-Cotes Formulas Introduce the basic idea of numerical integration and the newton-cotes method that replaces the function with an interpolation function over which the integration is performed URL
비디오 Integration: The Trapezoidal/composite Trapezoidal rule Introduce the Trapezoidal method which consists of integration over a line and a method of improving the result via several integration over several several intervals URL
비디오 Simpson's rules Introduce the simpson's 1/3 and 3/8 rules which consist of integration over second order and third order polynomials, respectively URL
비디오 Richardson Extrapolation Introduce the Richardson method which consists of using two less accurate integrals to obtain a more accurate result URL

연관 자료

loading..

사용자 의견

강의 평가를 위해서는 로그인 해주세요.

이용방법

  • 비디오 강의 이용시 필요한 프로그램 [바로가기]


    ※ 강의별로 교수님의 사정에 따라 전체 차시 중 일부 차시만 공개되는 경우가 있으니 양해 부탁드립니다.

이용조건