SylabUZ
Nazwa przedmiotu | Wstęp do metod numerycznych |
Kod przedmiotu | 11.0-WK-MATP-WMN-Ć-S14_pNadGenVW6K7 |
Wydział | Wydział Matematyki, Informatyki i Ekonometrii |
Kierunek | Mathematics |
Profil | ogólnoakademicki |
Rodzaj studiów | pierwszego stopnia z tyt. licencjata |
Semestr rozpoczęcia | semestr zimowy 2019/2020 |
Semestr | 5 |
Liczba punktów ECTS do zdobycia | 7 |
Typ przedmiotu | obieralny |
Język nauczania | polski |
Sylabus opracował |
|
Forma zajęć | Liczba godzin w semestrze (stacjonarne) | Liczba godzin w tygodniu (stacjonarne) | Liczba godzin w semestrze (niestacjonarne) | Liczba godzin w tygodniu (niestacjonarne) | Forma zaliczenia |
Ćwiczenia | 15 | 1 | - | - | Zaliczenie na ocenę |
Laboratorium | 15 | 1 | - | - | Zaliczenie na ocenę |
Wykład | 30 | 2 | - | - | Egzamin |
The goal of this course is to teach the basic theories and fundamentals of numerical methods and to give the student knowledge how to implement these methods for computer solutions of mathematical problems. Most of the applications are based on the use of mathematical software package (Matlab, Octave or Scilab). The course also provides an introduction to Matlab as well as practice in computer programming. Topics include analysis of errors, numerical linear algebra, solution of linear systems of equations and
nonlinear equations, interpolation and approximation by polynomials and numerical integration. Examples are taken from a wide variety of engineering situations.
Students attending classes are expected to pass the following courses:
1. Mathematical Analysis 1,2;
2. Linear Algebra 1,2;
Lecture
1. Computer Arithmetic
2. Solution of Nonlinear Equations
3. Solving Systems of Linear Equations
4. Interpolation and Polynomial Approximation
5. Numerical Integration
Class
1. Computer Arithmetic
2. Solution of Nonlinear Equations
3. Solving Systems of Linear Equations
4. Interpolation and Polynomial Approximation
Laboratory
1. Computer Arithmetic
2. Solution of Nonlinear Equations
3. Solving Systems of Linear Equations
4. Interpolation and Polynomial Approximation
Solving appropriate selected problems in the class and laboratory students can familiarize themselves with numerical methods provided during the lectures.
Opis efektu | Symbole efektów | Metody weryfikacji | Forma zajęć |
Verifying the level of preparation of students and their activities during the classes and laboratories.
Tests with tasks of different difficulty which help to assess whether students have achieved effects of the course in a minimum degree.
The assessment of the course consists of the grades of the exercises and laboratories (40%) and the written exam (60%). Student takes an exam under the condition of a positive evaluation of the exercise.
Student passes the course under the condition of a positive evaluation of the exercise, laboratory and written exam.
1. A.Björck, G.Dahlquist, Numerical Methods in Scientific Computing, SIAM, 2008.;
2. R.L.Burden, J.D.Faires, Numerical analysis, Prindle, Weber & Schmidt, Boston, Massachusetts, 1981;
3. J.Stoer, R.Bulirsch, Introduction to Numerical Analysis, Springer, 1993;
1. A.Quarteroni, R.Sacco, F.Saleri, Numerical mathematics, Springer, 2002;
2. A.Quarteroni, F.Saleri, Scientific Computing with Matlab and Octave, Springer, 2006;
3. P.Deuflhard, A.Hohmann Numerical analysis in modern scientific computing. An introduction, Springer, 2003;
Zmodyfikowane przez dr Alina Szelecka (ostatnia modyfikacja: 03-07-2019 12:06)