PřF:Bi8688 Introduction to Sci Comp - Course Information
Bi8688 Introduction to Scientific Computing
Faculty of ScienceAutumn 2014
- Extent and Intensity
- 1/1. 2 credit(s) (fasci plus compl plus > 4). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
- Teacher(s)
- prof. Walter Gander (lecturer), prof. RNDr. Jiří Hřebíček, CSc. (deputy)
prof. RNDr. Jiří Hřebíček, CSc. (alternate examiner) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: prof. RNDr. Jiří Hřebíček, CSc.
Supplier department: RECETOX – Faculty of Science - Prerequisites
- Passing the core courses of mathematical analysis
- Course Enrolment Limitations
- The course is offered to students of any study field.
- Course objectives
- At the end of this course the student will be able to understand what is contained in scientific computing using Maple and Matlab
- Syllabus
- Lecture 1. Finite Precision Arithmetic. Matlab, Octave, Maple . 1.1 Real Numbers and Machine Numbers 1.2 IEEE Standard, 1.3 Rounding Errors , Condition, Stability 1.4 Machine Independent Algorithms 1.5 Problems and Exercises Lecture 2. Linear Systems of Equations (direct and iterative solver) 2.1 Algorithms for dense Systems 2.2 Gaussian Elimination, Condition, Pivoting 2.3 LU and QR-decomposition 2.4 Algorithms for Large Sparse Systems 2.5 Classical Stationary Iterative Methods 2.6 Krylov Subspace Methods 2.7 Problems and Exercises Lecture 3. Nonlinear Equations . 3.1 Scalar Nonlinear Equations 3.2 Determinants and Zeros of Polynomials 3.3 Nonlinear Systems of Equations 3.4 Problems and Exercises Lecture 4. Least Squares Problems 4.1 Linear Least Squares Problem and the Normal Equations 4.2 Singular Value Decomposition (SVD) 4.3 Condition of the Linear Least Squares Problem 4.4 Algorithms Using Orthogonal Matrices 4.5 Nonlinear Least Squares Problems 4.6 Least Squares with Constraints 4.7 Problems and Exercises Lecture 5. Numerical Ordinary Differential Equations 5.1 Theoretical Background, Notation 5.2 Taylor Expansions, Truncation Error 5.3 Runge-Kutta Methods 5.4 Linear Multistep Methods 5.5 Special Cases 5.6 Problems and Exercise
- Literature
- recommended literature
- Gander, Walter, Gander, Martin J., Kwok, Felix. Scientific Computing - An Introduction using Maple and MATLAB. Springer, 2014.
- Teaching methods
- Lectures and following exercises
- Assessment methods
- The final evaluation will be a written test.
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course is taught only once.
The course is taught: in blocks.
Note related to how often the course is taught: 15.-19. prosince 2014.
General note: 15.-19. prosince 2014.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/sci/autumn2014/Bi8688