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Ternopil Ivan Puluj National Technical University

Факультет комп'ютерно-інформаційних систем і програмної інженерії

Кафедра комп'ютерних систем та мереж

Computing Techniques and Algorithms


Major 123 - Комп’ютерна інженерія (бакалавр)
Field of knowledge 12 Інформаційні технології
Academic degree bachelor's
Course type required
special education
Study start course 2
Semesters 3
Form of education full-time
Study hours structure
32– lectures
32– laboratory classes
Amount of hours for individual work 101
ECTS credits 5,5
Form of final examination exam
Academic degree PhD
Full name Tysh Ievgeniia
Prerequirements (prerequisite courses)
Higher mathematics, programming 
Course goals and learning objectives
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. 
Course description
Lectures 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 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.
Assessment criteria
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. 
Recommended reading list. Subject Resources

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.

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. 
Course author
PhD Tysh Ievgeniia 
Дата останнього оновлення: 2020-12-15 17:23:32