230-0261/02 – Interpolation and Approximation of Functions (IaAF)

Gurantor departmentDepartment of MathematicsCredits10
Subject guarantordoc. RNDr. Pavel Kreml, CSc.Subject version guarantordoc. RNDr. Pavel Kreml, CSc.
Study levelpostgraduateRequirementChoice-compulsory type B
YearSemesterwinter + summer
Study languageEnglish
Year of introduction2019/2020Year of cancellation
Intended for the facultiesFAST, FBI, FS, FMT, USP, HGF, FEIIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
KRE40 doc. RNDr. Pavel Kreml, CSc.
STA50 RNDr. Jana Staňková, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Examination 2+0
Part-time Examination 2+0

Subject aims expressed by acquired skills and competences

Main study goals: (i) to be acquainted with actual progress in this mathematical discipline, (ii) to extend needed theoretical knowledge with emphasized orientation to its applica-bility, (iii) to increase communication ability of specialists in different branches. With regard to professional orientation of students learning themes modification is offered to fulfill presented aims.

Teaching methods

Seminars
Individual consultations
Other activities

Summary

These lectures deal with methods for constructing approximating functions for any set of data by using polynomial interpolation, least-squares approximation and Chebyshev approximation. There are compared several ways of doing interpolation and there are contrasted these procedures with several ways for fitting imprecise data and for drawing smooth curves. It is shown how can help symbolic algebra computer algebra programs in obtaining interpolating and least-squares polynomials.

Compulsory literature:

Gerald,F.-Wheatley,P.: Applied Numerical Analysis. Addison Wesley 1994. Stoer,J. - Bulirsch,R.: Introduction to Numerical Analysis. Springer-Verlag, New York 1993. Boháč, Zdeněk: Numerical Methods and Statistics, VŠB – TUO, Ostrava 2005, ISBN 80-248-0803-X

Recommended literature:

http://mdg.vsb.cz/portal/nm/nm.pdf

Way of continuous check of knowledge in the course of semester

Continuous work on project. Using aproximation and interpolation methods. Examination.

E-learning

http://www.studopory.vsb.cz http://mdg.vsb.cz/portal/nm/index.php (in Czech language) Gerald,F.-Wheatley,P.: Applied Numerical Analysis., Addison Wesley 1994. Stoer,J. – Bulirsch,R.: Introduction to Numerical Analysis., Springer-Verlag, New York 1993.

Other requirements

Each student must discharge: a) examples, b) project.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Syllabus 1. Kinds of: - dependence and independence of functions, - existence and definiteness of approximating functions, - error of approximation. 2. Polynomial interpolation: -the error estimate of the interpolation, - Lagrangian and Mewton polynomials, - extrapolation, interpolation of rational functions, - choice of points for fitting. 3. Interpolating with a spline functions : - interpolating with a cubic spline, - features of cubic spline, - B-spline curves, - Bezier curves. 4. Orthogonal system of functions: - orthogonal polynomials, - Chebyshev, Hermitov, Gramov polynomials. 5. Least-squares approximations: - the best L2- approximation, least-squares method, - normal equations, solving sets of linear equations, - algorithm of least-squares method, - nonlinear data. 6. Chebyshev approximation: - the best uniform approximation, - algorithm of the method, maximum error.

Conditions for subject completion

Part-time form (validity from: 2019/2020 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Examination Examination   3
Mandatory attendence participation:

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Conditions for subject completion and attendance at the exercises within ISP:

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