بسم الله الرحمن الرحيم Islamic University of Gaza Electrical Engineering Department

Engineering Analysis (EELE 3301) By Basil Hamed, Ph. D. Control Systems Engineering www.iugaza.edu/homes/bhamed http://site.iugaza.edu.ps/bhamed/

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 e-mail : bhamed@ iugaza.edu bahamed@hotmail.com WebSite : http://site.iugaza.edu.ps/bhamed/ Phone : 2860700 Ext. 2875 Meeting : (Sat Mon Wed) 12:00-1:00 (K 108)

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)

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

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

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

Course Syllabus Grading System: Homework & Quizzes 20 % Mid term Exam (13/11/2018) 1:00-2:00 30 % Final Exam (14/1/2019) 11:00-1:00 50 % 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.

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

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:

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

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