Syllabus for Scientific Computing KF
A revised version of the syllabus is available.
- 5 credits
- Course code: 1TD399
- Education cycle: First cycle
Main field(s) of study and in-depth level:
Computer Science G1N,
Explanation of codes
The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:
- G1N: has only upper-secondary level entry requirements
- G1F: has less than 60 credits in first-cycle course/s as entry requirements
- G1E: contains specially designed degree project for Higher Education Diploma
- G2F: has at least 60 credits in first-cycle course/s as entry requirements
- G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
- GXX: in-depth level of the course cannot be classified
- A1N: has only first-cycle course/s as entry requirements
- A1F: has second-cycle course/s as entry requirements
- A1E: contains degree project for Master of Arts/Master of Science (60 credits)
- A2E: contains degree project for Master of Arts/Master of Science (120 credits)
- AXX: in-depth level of the course cannot be classified
- Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Established: 2011-03-10
- Established by: The Faculty Board of Science and Technology
- Revised: 2015-05-27
- Revised by: The Faculty Board of Science and Technology
- Applies from: Autumn 2015
- Entry requirements:
- Responsible department: Department of Information Technology
To pass, the student should be able to
- describe and perform tasks in connection to the key concepts covered in the course;
- explain the idea behind and apply the algorithms covered in the course;
- explore properties for numerical methods and mathematical models by using the analysis methods covered in the course;
- explain the results when running a MATLAB program, and describe a problem with an algorithm or a programming code in MATLAB (which might include self-written MATLAB functions);
- structure and divide a computational problem into sub-problems, formulate an algorithm and implement the algorithm in MATLAB;
- in a short report, in Swedish and English, explain and summarise solution methods and results in a lucid way.
MATLAB and programming in MATLAB: fundamental programming structures (if statements, for, while), functions, parameter passing. Programming structure. Problem solving methodology. Given a problem, divide it into sub-problems, write an algorithm and transform the algorithm to a MATLAB program.
Basic matrix and vector operations. Expressing linear systems of equations in matrix vector form. Matrices and vectors as mathematical objects and data structures. Solution to linear equation systems using LU-factorisation with pivoting. Norms for matrices and vectors. Sensitivity and condition number, stable/unstable algorithm. Numerical solution to integrals. Simpsons metod and Trapezoid rule. Solution to non-linear equations and iterative methods. Bisection, Newton-Raphon method and hybrid algorithms. Floating point representation and the IEEE-standard for floating point arithmetic, machine epsilon and round-off error.
Important key concepts covered in the course e.g. algorithm, numerical method, complexity, discretisation och discretisation error, machine epsilon, floating point numbers, round off error, accuracy and order of accuracy, stable and unstable algorithm, iteration and iterative method, condition and condition number, efficiency, adaptivity and adaptive methods, convergence, convergence rate, fix point iteration.
Lectures, workouts (problem solving classes), laboratory work, mini projects.
Written examination (3 credits) and mini projects presented in writing (2 credits).
- Latest syllabus (applies from Autumn 2020)
- Previous syllabus (applies from Autumn 2019)
- Previous syllabus (applies from Autumn 2017)
- Previous syllabus (applies from Spring 2017)
- Previous syllabus (applies from Autumn 2015)
- Previous syllabus (applies from Autumn 2013)
- Previous syllabus (applies from Spring 2011)
- Previous syllabus (applies from Autumn 2010, version 2)
- Previous syllabus (applies from Autumn 2010, version 1)
Applies from: Autumn 2015
Some titles may be available electronically through the University library.
Chapra, Steven C.
Applied numerical methods with MATLAB for engineers and scientists
3. international ed.: Boston: McGraw-Hill Higher Education, 2012