ECSE 305 F10 Course Outline1

ECSE 305 F10 Course Outline1 - ECSE 305 Fall 2010...

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ECSE 305 - Fall 2010 Probability and Random Signals I (3 cr.) Senate on January 29, 2003 approved a resolution on academic integrity, which requires that the following reminder to students be printed on every course outline: McGILL UNIVERSITY VALUES ACADEMIC INTEGRITY. THEREFORE ALL STUDENTS MUST UNDERSTAND THE MEANING AND CONSEQUENCES OF CHEATING, PLAGIARISM AND OTHER ACADEMIC OFFENCES UNDER THE CODE OF STUDENT CONDUCT AND DISCIPLINARY PROCEDURES (see http://www.mcgill.ca/integrity for more information). General Information: Instructor: Prof. Benoît Champagne Office: McConnell Engineering Building, Room 756 Tel: (514) 398-5701 Email: [email protected] Office Hours: o Monday & Wednesday from 1:30 to 3:30pm o Otherwise by appointment Lectures: Monday, Wednesday and Friday: from 12:30 to 13:30 Location: Room ENGMC 13 Lectures will start on Wednesday, September 1 st , 2010 Tutorials: There are two tutorial sections for this course: o CRN497 (Sec003): Friday, 09:30 to 11:30, ENGTR 1090 o CRN498 (Sec004): Monday, 09:30 to 11:30, ENGTR 1080 The tutorials will begin on Friday September 10. During each tutorial, the responsible TA will solve representative problems related to material recently covered in class. Teaching Assistants: Name Office Main Duty Email Reza Abdolee MC751 Tutorials [email protected] Siavash Rahimi MC751 Tutorials [email protected] B. champagne Page 1 9/3/2010
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Course Description: Prerequisite: ECSE-303 (Signals and Systems I) or ECSE-306 (Fundamentals of Signals and Systems). No previous exposure to probability is assumed. Objectives: The course is intended as an introduction to the mathematical theory and applications of probability and random signals for students in electrical, computer and software engineering. It aims to develop fundamental concepts and methods of this field and, through a variety of examples, illustrate some of their applications. After successfully completing the course, students should be well prepared to take on more advanced courses in such fields as communications systems, artificial intelligence, computer network, control engineering and signal processing. List of Topics: Part I : Fundamental concepts (~9 hours) Introduction : Determinism and randomness in science, regularity and relative frequency, goals of probability, axiomatic approach. Background material : Review of set theory: terminology, set operations, and sigma-algebra. Combinatorial analysis: counting principles, permutations, combinations, related results.
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