Computer Aided Analysis and Design

Course Description

The role of computers in analysis and design of technical systems is presented. The course describes error handling in computer calculations, linear system solving algorithms and numerical optimization algorithms, as well as evolutionary algorithms. The transient analysis formulations and methods are presented. The systems behaviour is analysed in regard of system stability and chaotic properties. The presented algorithms are evaluated in regard of their computational efficiency.

Learning Outcomes

  1. identify an optimization problem
  2. apply a nonlinear optimization procedure
  3. compare different optimization algorithms
  4. define floating point precision standard
  5. describe the problem of solving differential equations systems
  6. apply a numerical integration method
  7. compare the precision and stability of numerical integration methods

Forms of Teaching

Lectures

predavanja

Exercises

auditorne vjezbe

Independent assignments

domaca zadaca

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Homeworks 0 % 25 % 0 % 25 %
Mid Term Exam: Written 0 % 35 % 0 %
Final Exam: Written 0 % 40 %
Exam: Written 50 % 50 %
Exam: Oral 25 %

Week by Week Schedule

  1. The Gaussian Elimination Method (GEM); LU Factorization
  2. Pivoting Strategies; PLU Factorization
  3. Optimization in one dimension (golden section search, successive parabolic interpolation, Newton's method)
  4. Nonlinear unconstrained optimzation
  5. Nonlinear constrained optimzation
  6. Direct Search Algorithms (the Hooke-Jeeves method); Gradient Methods (the steepest descent);
  7. Nonlinear Least-Squares Problems; The Gauss-Newton Method; The Levenberg-Marquardt Method
  8. Midterm exam
  9. Stochastic search (simulated annealing, genetic algorithms, Monte Carlo search), Evolutionary algorithms for SOOP
  10. Numerical solving of differential equations; Euler's method; Taylor's method
  11. Multistep Methods; Multivalue Methods
  12. Multistep Methods; Multivalue Methods
  13. Floating point precision and error propagation
  14. Floating point precision and error propagation
  15. Final exam

Study Programmes

University graduate
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Core-elective courses (1. semester) (3. semester)
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Elective Courses (1. semester) (3. semester)
[FER3-HR] Electric Machines, Drives and Automation - profile
Elective Courses (1. semester) (3. semester)
[FER3-HR] Electronic and Computer Engineering - profile
Elective Courses (1. semester) (3. semester)
[FER3-HR] Electronics - profile
Elective Courses (1. semester) (3. semester)
[FER3-HR] Information and Communication Engineering - profile
Elective Courses (1. semester) (3. semester)
[FER3-HR] Network Science - profile
Elective Courses (1. semester) (3. semester)
[FER3-HR] Software Engineering and Information Systems - profile
Elective Courses (1. semester) (3. semester)
[FER2-HR] Computer Engineering - profile
Specialization Course (1. semester) (3. semester)
[FER2-HR] Computer Science - profile
Specialization Course (3. semester)
Theoretical Course (1. semester)
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Specialization Course (1. semester) (3. semester)
[FER2-HR] Telecommunication and Informatics - profile
Recommended elective courses (3. semester)

Literature

L. Budin (.), Analiza i projektiranje računalom - skripta, Skriptarnica
S. Turk, L. Budin (1989.), Analiza i projektiranje računalom, Školska knjiga, Zagreb

For students

General

ID 240680
  Winter semester
5 ECTS
L1 English Level
L1 e-Learning
60 Lectures
0 Seminar
0 Exercises
15 Laboratory exercises
0 Project laboratory

Grading System

Excellent
Very Good
Good
Sufficient