Course detail

Computer-supported solution of engineering problems

FEKT-NPPRAcad. year: 2017/2018

Interpretation of numerical methods, implemented in widely-utilized CAD programs, is given. This course covers essential methods of solving both linear and nonlinear problems. Within each group, methods are classified according to their features and practical applicability. The comment is then centred on the well proven methods. For these methods, also the MATLAB source code is available in computer exercises.

Language of instruction

English

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

prof. Ing. Jiří Mišurec, CSc.

Department

Department of Telecommunications (UTKO)

Learning outcomes of the course unit

Active knowledge of mathematic numerical methods of solving frequent practical problems as a precondition of effective utilization of professional programs, to which these methods are included.

Prerequisites

The subject knowledge on the Bachelor´s degree level is requested.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Techning methods include lectures, computer laboratories and practical laboratories. Course is taking advantage of e-learning (Moodle) system.

Assesment methods and criteria linked to learning outcomes

Requirements for completion of a course are specified by a regulation issued by the lecturer responsible for the course and updated for every.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

To elaborate actual and to acquire more of the knowledge about the practically exploitable numerical methods of solving engineering problems with a view to electrical engineering, about the corresponding algorithms of computer solution, and about the efficient utilization of professional programs as MicroCap, PSPICE, SNAPwhere these algorithms are implemented and possibilities of using numeric methods by spreadsheet programs.

Specification of controlled education, way of implementation and compensation for absences

The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

ACTON, F.S.: Numerical Methods that Work. The Mathematical Association of America, Washington D.C., 1990. ISBN 0-88385-450-3.
PRESS,W.H. et al.: Numerical Recipes in Pascal. The Art of Scientific Computing. Cambridge University Press, 1994. ISBN 0-521-37516-9 (book), 0-521-37532-0 (CD).

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme EECC-MN Master's

    branch MN-TIT , 2 year of study, winter semester, elective specialised
    branch MN-EST , 1 year of study, winter semester, elective interdisciplinary

  • Programme AUDIO-PU Master's

    branch PU-AUD , 2 year of study, winter semester, elective interdisciplinary

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

prof. Ing. Jiří Mišurec, CSc.

Syllabus

Introduction to computer solution of electronic circuits.
Principles of numeric and symbolic methods.
Methods of analyze linear circuits.
Heuristic and algorithmic methods.
Matrix algorithmic methods.
Graph algorithmic methods.
Symbolic analysis of systems in the operator domain.
Semisymbolic and numerical analysis of systems.
Solving the sets of nonlinear algebraic equations.
Solving the sets of nonlinear differential equations.
Approximation, interpolation and extrapolation.
Computer models of circuit electronic elements.

Exercise in computer lab

26 hod., compulsory

Teacher / Lecturer

prof. Ing. Jiří Mišurec, CSc.

Syllabus

Basic and special matrix operations in MATLAB.
Numeric and symbolic algorithms.
Solving electronic circuits by spreadsheet program.
Simulation by MicroCap.
Simulation by PSPICE.
Working on project.
Roots finding of characteristic polynomials.
Working on project.
Algorithms of symbolic and semisymbolic analyses.
Simulation by SNAP.
Working on project.
Approximation of functions.