COMPUTER ENGINEERING
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
MAT3012	Numerical Analysis	Spring	2	2	3	6

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Hybrid
Course Coordinator :	Dr. Öğr. Üyesi LAVDİE RADA ÜLGEN
Course Lecturer(s):	Dr. UTKU GÜLEN Dr. Öğr. Üyesi ERKUT ARICAN RA ÇİĞDEM ERİŞ Dr. Öğr. Üyesi LAVDİE RADA ÜLGEN
Recommended Optional Program Components:	None
Course Objectives:	Numerical Analysis is concerned with the mathematical derivation, description and analysis of obtaining numerical solutions of mathematical problems. We have several objectives for the students. Students should obtain an intuitive and working understanding of some numerical methods for the basic problems of numerical analysis. They should gain some appreciation of the concept of error and of the need to analyze and predict it. Topics cover linear and nonlinear system of equations, interpolation, curve fitting using least-squares method integration, eigenvalue, and singular value decomposition. And also they should develop some experience in the implementation of numerical methods by using MATLAB.

Learning Outcomes

The students who have succeeded in this course;
1. Define errors, big O notation, use Taylor’s theorem
2. Solve nonlinear algebraic equations
3. Solve linear systems and to use iterative methods for linear systems
4. Solve systems of nonlinear algebraic equations
5. Use interpolation methods and polynomial approximation for a given data, piecewise linear interpolation and spline function interpolation;
6. Use least-squares method for curve fitting
7. Calculate maximum eigenvalues and corresponding eigenvectors and to calculate singular value decomposition of a matrix and apply it on image processing
8. Implement numerical methods on MATLAB and test their programs behavior through expected results in accordance with the Numerical Analysis theory.

Course Content

The course studies algorithms and computer techniques for solving mathematical problems. They do all computations using MATLAB.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to Numerical Analysis: kinds of problems we solve. Error analysis, round-off and truncation errors. Taylor Theorem and Taylor series.
2)	Loss of Significance Big O notation
3)	Solution of Nonlinear Equations, i.e. f(x)=0. Bracketing Methods for Locating a Root. Bisection (Method of Bolzano). False-position (Regula-Falsi) Method.
4)	Newton-Raphson Method (Applications from thermodynamics, fluid mechanics, and electronics)
5)	Solution of Linear Systems of Equations. Properties of Vectors and Matrices. Upper-Triangular Linear Systems. Gaussian Elimination and Pivoting.
6)	Triangular Factorization (LU Decomposition)
7)	Iterative Methods for Linear Systems. Jacobi Method. Gauss-Sedidel Method.
8)	Iterative Methods for Linear Systems Gauss-Sedidel Method. Diagonally dominant matrix. Errors is solving linear systems.
9)	System of Nonlinear Equations (Newton’s Method)
10)	Interpolation and Polynomial Approximation. Introduction to Interpolation. Lagrange Approximation.
11)	Newton Interpolation Polynomials. Piecewise Linear Interpolation, Cubic Spline Functions
12)	Curve Fitting (Applications from heat transfer and electrical engineering). Least-Squares Approximation. Linearization of Nonlinear Relationships.
13)	Eigenvalues and Eigenvectors. The power method
14)	Singular Value decomposition. Applications from Image Processing

Sources

Course Notes / Textbooks:

Stephen C. Chapra, Applied Numerical Methods W/MATLAB: for Engineers & Scientists, 3rd Edition, McGrawHill

References:

• J. Douglas Faires and Richard L. Burden, Numerical Methods, Brooks/Cole Publishing Co., 4th Edition, 2013.
• Applied Numerical Methods Using MATLAB, Won Young Yang, Wenwu Cao, Tae-Sang Chung, John Morris.
• John H. Mathews and Kurtis D. Fink Numerical Methods Using MATLAB, Pearson, 2004. ISBN 0-13-191178-3
• Mustafa Bayram, Nümerik Analiz, Sürat Üniversite Yayınları, 3. Baskı, 2013.
• İrfan Karagöz, Sayısal Analiz ve Mühendislik Uygulamaları, Nobel Yayın Dağıtım, ISBN: 978-605-395-077-6.
• Ömer Akın, Nümerik Analiz, Ankara Üniversitesi Basımevi, 1998, ISBN: 975-482-448-7

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	3	% 10
Homework Assignments	1	% 10
Midterms	1	% 35
Final	1	% 45
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 55
PERCENTAGE OF FINAL WORK		% 45
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	2	28
Laboratory	14	2	28
Study Hours Out of Class	14	2	28
Homework Assignments	1	4	4
Quizzes	3	1	3
Midterms	1	2	2
Final	1	2	2
Total Workload			95

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Adequate knowledge in mathematics, science and computer engineering; the ability to use theoretical and practical knowledge in these areas in complex engineering problems.	5
2)	Ability to identify, formulate, and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose.	5
3)	Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose.
4)	Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in computer engineering applications; ability to use information technologies effectively.
5)	Ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or computer engineering research topics.
6)	Ability to work effectively within and multi-disciplinary teams; individual study skills.
7)	Ability to communicate effectively in verbal and written Turkish; knowledge of at least one foreign language; ability to write active reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8)	Awareness of the necessity of lifelong learning; ability to access information, to follow developments in science and technology and to renew continuously.
9)	To act in accordance with ethical principles, professional and ethical responsibility; information on the standards used in engineering applications.
10)	Information on business practices such as project management, risk management and change management; awareness of entrepreneurship and innovation; information about sustainable development.
11)	Knowledge of the effects of engineering practices on health, environment and safety in the universal and social scale and the problems of the era reflected in engineering; awareness of the legal consequences of engineering solutions.