Course Code: EA2203 • Study year: II • Academic Year: 2024-2025
Domain: Electronic engineering and telecommunications • Field of study: Applied Electronics
Type of course: Compulsory
Language of instruction: English
Erasmus Language of instruction: English
Name of lecturer: Valer Daniel Breaz
Seminar tutor: Ioan Lucian Popa
Form of education Full-time
Form of instruction: Class
Number of teaching hours per semester: 56
Number of teaching hours per week: 4
Semester: Summer
Form of receiving a credit for a course: Grade
Number of ECTS credits allocated 5

Course aims:

Introducing basic concepts and methods of numerical analysis.
Initiating students in methods of numerical programming for solving mathematical problems and for start using numerical software. Students have to know the fundamental concepts of numerical analysisand various numerical algorithms.
These specific objectives allow modeling and solving complex problems using knowledge of mathematics and informatics.

Course Entry Requirements:


Course contents:

1. Elements of approximation theory and matrix analysis 1.1 Analysis and evaluation of arithmetic expressions 1.2 Items of errors theory and floating point arithmetic 1.3 Calculating the determinant and inverse of a matrix 2. Methods and numerical algorithms. Differences calculus 2.1 Gauss elimination method 2.2 Total elimination method 3. Functions approximations 3.1 Cholesky method 3.2 Onicescu method 3.3 Iterative methods 3.4 Successive approximations method 3.5 Tangent method 3.6 Secant method 4. Numerical differention and integration algorithms 4.1 Bairstrov method 4.2 Finite differences methods 4.3 Divided differences methods 5. Numerical algorithms for solving algebraic equations 5.1 Approximation in mean square 5.2 Numerical differentiation 6. Items of Symbolic Calculus 6.1 Quadrature formulas of Gauss and Newton Cotes type 6.2 Numerical integration using Taylor series 6.3 Multipas methods

Teaching methods:

Lecture, discussion, exemplification.

Learning outcomes:

In order to obtain credits for this discipline, the students have to operate with elementary items of numerical analysis and use soft for solving different mathematical problems.

Learning outcomes verification and assessment criteria:

Final evaluation – 50%; Laboratory activities – 50%.

Recommended reading:

Eugen K. Blum, Numerical Analysis and Computation: Theory and Practice, Addison-Wesley, 1972, -.
R.L. Burden, L.J. Faires, Numerical Analysis, PWS Kent, 1986,
S. Nakamura, Numerical Analysis and Graphic Visualization in MATLAB, Pretice-Hall, 1996,