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Numerical Analysis (Spring 2008) |
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| Course code : | ENUMA-U01 | ||
| ECTS Credits : | 7,5 | Status : | Optional for specified Programme |
| Placement : | 5-7 semester | Hours per week : | 4 |
| Length : | 1 semester | Teaching Language : | English if English students are present |
| Principal Content : | Curve Fitting. (Ex: Finding a polynomial expression y = p(x) defining y in terms of x when only a set of samples/measurements (x,y) are given. This is relevant when DC/AC conversion is performed in signal processing.) Interpolation. Ortogonal Polynomials. Splines. Least Squares Regression. Numerical Integration and Differentiation. (Ex: Solving a definite integral when no antiderivative exists. This is relevant for the calculation of probabilities whenever we are dealing with the normal distribution in the processing of random signals.) Trapezoidal Rule Simpson´s Rule Gaussian Quadrature. Richardson Extrapolation. Roots of nonlinear equations. (Ex: Finding the zeros and poles of a transfer function of a filter.) Newton-Raphson for systems of nonlinear equations. Bairstow´s Method. Optimization. (Finding the local minima of a function of several variables. Ex: Design of neural networks.) Conjugate Gradient Methods. Quasi Newton Methods. Ordinary Differential Equations. (Extremely relevant, since only a limi-ted proportion of real-life differential equations have solutions which can be determined by use of classical mathematics.) One Step Methods. Runge Kutta Methods. Multistep Methods. Predictor-Corrector Methods. | ||
| Teaching method : | Lectures, classroom exercises, computerbased assignments. Group Work. | ||
| Required prequisites : | Documented knowledge corresponding to DSM3/DSM4 and OOP1 | ||
| Responsible teacher : | Hans Pedersen
, hchpe@dtu.dk |
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