Силабус

Ternopil Ivan Puluj National Technical University

Каф. комп'ютерних систем та мереж

Computing Techniques and Algorithms

syllabus

1. Educational programs for which discipline is mandatory:

# Educational stage Broad field Major Educational program Course(s) Semester(s)
1 bachelor's 12. Інформаційні технології 123. Комп’ютерна інженерія (бакалавр) 2 3

2. The course is offered as elective for all levels of higher education and all educational programs.

3. Information about the author of the course

Full name Tysh Ievgeniia
Academic degree PhD
Academic title none
Link to the teacher`s page on the official website of the University http://library.tntu.edu.ua/personaliji/a/t/tysh-jevhenija-volodymyrivna/
Е-mail (in the domain tntu.edu.ua)

4. Information about the course

Study hours structure Lectures: 32
Practical classes: 0
Laboratory classes: 32

Amount of hours for individual work: 101
ECTS credits: 5,5
Teaching language english
Form of final examination exam
Link to an electronic course on the e-learning platform of the university https://dl.tntu.edu.ua/bounce.php?course=4824

5. Program of discipline

Description of academic discipline, its goals, subject of study and learning outcomes

The purpose of teaching the discipline "Algorithms and Computing Techniques":
- to form the basic knowledge, skills and abilities of students in the basics of computational mathematics as a scientific and applied discipline, which will be sufficient for the further continuation of education and self-education in the field of computer networks and neighboring areas;
- to give an idea of the role and place of computational mathematics and algorithm specialist when setting up, choosing effective algorithms and interpreting the results of the solution of tasks in the field of designing and operating computer networks.

The place of academic discipline in the structural and logical scheme of study according to the educational program

Prerequisites. List of disciplines, or knowledge and skills, possession of which students needed (training requirements) for successful discipline assimilation

Higher mathematics, programming

Contents of the academic discipline

Lectures (titles/topics)

Theme 1. Fundamentals of algorithm theory. Elements of error theory.
Theme 2. Algorithm strategies
Theme 3. The concept of algorithmic strategies. Brute force algorithms, greedy algorithms, "distribute and conquer", return algorithms.
Theme 4. Building algorithms.
Theme 5. Solution of system of linear Equations.
Theme 6. Numerical methods for solving nonlinear algebraic equations.
Theme 7. Interpolation. Polynomial Interpolation. Lagrange Interpolation Formula. Interpolation Error. Newton’s Formula. Interpolation by Spline Functions.
Theme 8. Approximation of functions. Least Squares Approximation.
Theme 9. Numerical integration. Numerical differentiation.
Theme 10. Solution of first order and second order ordinary differential equations.
Theme 11. Boundary value problem.
Theme 12. Tasks of mathematical physics.
Theme 13. Linear programming.
Theme 14. The Simplex Method.
Theme 15. Transport task.
Theme 16. Theory of games.

Laboratory classes (topics)

Solution of linear algebraic equations’ systems.
Approximate methods for solving nonlinear algebraic equations.
Interpolation of functions.
Estimation of linear regression parameters by least squares method.
Numerical integration.
Numerical differentiation.
Numerical integration of ordinary differential equations of the first order solved with respect to the derivative by one-step methods. Solving the Cauchy problem.
Numerical integration of ordinary differential equations of second order. The solution of the boundary value problem.
The solution of the linear programming problem by graphic method.
Search for the initial support plan.
Simplex method for solving the linear programming problem.

Learning materials and resources

Basic

1. Gerald, C. F., Wheatly, P. O. Applied Numerical Analysis. / C. F. Gerald, P. O. Wheatly. – Pearson, 2003. – 624.
2. Shen, Wen. An Introduction to Numerical Computation. / Wen Shen. – World Scientific Publishing Company, 2015. – 268.
3. Jain, M. K., Iyengar, S. R. K.,Jain, R. K. Numerical Methods for Scientific and Engineering Computation. / M. K. Jain, S. R. K. Iyengar, R. K. Jain. –New Delhi etc., Wiley Eastern Ltd., 1985. – 406.
4. Conte, S.D., deBoor, C. Elementary Numerical Analysis: An Algorithmic Approach. / S.D. Conte, C. deBoor. – McGrawHill, New York, 1981. – pp. 153-157.
5. Krishnamurthy, E. V., Sen, S. K. Applied Numerical Analysis. / E.V. Krishnamurthy, S.K. Sen. – East West Publication, 2006. – 508.
6. Polyanin, A.D., Zaitsev, V.F. Handbook of Exact Solutions for Ordinary Differential Equations (2nd edition) / A.D. Polyanin, V.F. Zaitsev. – Chapman & Hall/CRC Press, Boca Raton, 2003. – 802.
7. Polyanin, A.D. Handbook of Linear Partial Differential Equations for Engineers and Scientists. / A.D. Polyanin. – Chapman & Hall/CRC Press, Boca Raton, 2002. – 800.
8. Murty, Katta G. Linear programming. / Katta G. Murty – Wiley, 1983. – 512.

Additional
1. Watson, G.A. Approximation theory and numerical methods. / G.A. G.A. – Chichester : New York John Wiley and Sons, 1997. – 229.
2. Dutta, Prajit K. Strategies and games: theory and practice. / Prajit K. Dutta. – MIT Press, 1999. – 476.
3. Fernandez, L.F., Bierman, H.S. Game theory with economic applications. / L.F. Fernandez, H.S. Bierman. – Pearson, 1997. – 480.
4. Gibbons, Robert D. Game theory for applied economists. / Robert D. Gibbons. – Princeton, N.J. : Princeton University Press, 1992. – 267.
5. Dantzig, G.B. Linear Programming and Extensions. / G.B. Dantzig. –Princeton University Press, Princeton, NJ, 1963. – 627.
6. Harrington, Joseph E. Games, strategies, and decision making. / Joseph E. Harrington. – Worth Publishers, 2008. – 540.
7. Isaacs, Rufus. Differential Games: A Mathematical Theory With Applications to Warfare and Pursuit, Control and Optimization. / Rufus Isaacs. – New York: Dover Publications, 1999. – 416.
8. Shoham, Yoav, Leyton-Brown, Kevin. Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations. / Yoav Shoham, Kevin Leyton-Brown. – New York: Cambridge University Press, 2009. – 532.

6. Policies and assessment process of the academic discipline

Assessment methods and rating system of learning results assessment

Module 1 - 40 points (theoretical classes (tests)-20, practical classes-20), Module 2 - 35 points (theoretical classes (tests)-20, practical classes-15). Form of final term control – examination.


Table of assessment scores:

Assessment scale
VNZ
(100 points)
National
(4 points)
ECTS
90-100 Excellent А
82-89 Good B
75-81 C
67-74 Fair D
60-66 E
35-59 Poor FX
1-34 F
Approved by the department
(protocol №
on «
»
y.).