1. بسم الله الرحمن الرحيم Islamic University of Gaza Electrical Engineering Department

2. Engineering Analysis (EELE 3301)By
Basil Hamed, Ph. D.
Control Systems Engineering

3. Faculty of Engineering Department of Electrical Engineering
Course Syllabus
Islamic University of Gaza
Faculty of Engineering
Department of Electrical Engineering
Engineering Analysis(EELE 3301)
Pre-Requisite: Calculus C (MATHC 2301)
Instructor : Basil Hamed, Ph.D. Control Systems Engineering
Office : B336
iugaza.edu
WebSite :
Phone : Ext. 2875
Meeting : (Sat Mon Wed) 12:00-1:00 (K 108)

4. Course Syllabus
Course Description: Engineering Analysis covers topics in Linear Algebra, a very useful branch of mathematics in physics, economics, social sciences, natural sciences, and engineering, and the basics of MATLAB, a powerful computing language for solving linear algebra problems and much more. Specific topics include solving systems of linear equations, linear independence, linear transformations, matrix inverses, vector spaces, and least-squares problems. Due to its broad range of applications, linear algebra is one of the most widely taught subjects in college-level mathematics
Prerequisite: Calculus C (MATHC 2301)

5. Course Syllabus
Text Book: Linear Algebra with Applications, Ninth Edition by Steven J. Leon 2015
References:
Elementary Linear Algebra with Applications and Labs by Bernard Kolman and David R. Hill
Linear Algebra and Its Applications, 4th Edition by David C. Lay
Linear Algebra And Its Applications by Lay D.C.
Introduction to linear algebra by Marcus M., Minc H.
A first course in linear algebra, with concurrent examples by Hamilton A.G.
A course in linear algebra with applications by Derek J. S. Robinson

6. Course Syllabus Course Goals:
After successfully completing the course, you will have a good understanding of the following topics and their applications:
Systems of linear equations
Row reduction and echelon forms
Matrix operations, including inverses
Linear dependence and independence
Orthogonal bases and orthogonal projections
Linear models and least-squares problems
Determinants and their properties
Cramer's Rule
Eigenvalues and eigenvectors
Diagonalization of a matrix
Symmetric matrices
Similar matrices
Linear transformations

7. Course Syllabus Materials Covered: Matrices and Systems of Equations
Determinants
Vector Spaces
Linear Transformations
Orthogonality
Eigenvalues
Numerical Linear Algebra

8. Course Syllabus Grading System:
Homework & Quizzes % Mid term Exam (13/11/2018) 1:00-2: %
Final Exam (14/1/2019) 11:00-1: %
Homework
Homework assignments are to be returned on time. No excuses will be accepted for any delay.
Office Hours
Open-door policy, by appointment or as posted.

9. What is a Matrix?
A matrix is a set of elements, organized into rows and columns
rows
columns

10. Basic concepts Vector in Rn is an ordered set of n real numbers.
e.g. v = (1,6,3,4) is in R4
A column vector:
A row vector:
m-by-n matrix is an object in Rmxn with m rows and n columns, each entry filled with a (typically) real number:

11. Basic Matrix Operations
Addition, Subtraction, Multiplication: creating new matrices (or functions)
Just add elements
Just subtract elements
Addition and subtraction must be done in same dimension
Do multiplication together
Multiply each row by each column

12. See You next Monday