BLM220 DISCRETE MATHEMATICS Syllabus
Department: Computer Engineering
Course Name: BLM220, Discrete Mathematics, (3+0) 3 hours lecture Instructor: Hakan Kutucu
Office: Faculty of Engineering, Room No: M334 Tel: 433 20 21 / 1590
E-mail: [email protected] Office Hours: Thursday 13:30-15:00 Textbook:
1. Rosen, Kenneth H.; 2007; “Discrete Mathematics and its Applications”; 6th Ed.;
McGraw-Hill
This is an excellent and well written book. It is used in a large number of universities in engineering, computer science and mathematics courses. In addition, there are excellent resources available online – see www.mhhe.com/math/advmath/rosen/r5/
References:
1. Stein, Clifford, Drysdale, Robert L., Bogart, Kenneth; 2011; “Discrete Mathematics for Computer Scientists”; Pearson
2. James A. Anderson; 2003; “Discrete Mathematics with Combinatorics”, 2nd Ed.;Prentice Hall
Course Focus: The focus of this course is on basic mathematical concepts in discrete mathematics and on applications of discrete mathematics in algorithms and data structures. To teach the problem solving strategies, techniques, and tools. To show students how discrete mathematics can be used in modern computer science (with the focus on algorithmic applications).
Prerequisites: Basic Mathematics Skills Grading:
Midterm I %25
Midterm II %25
Final Exam %50 Attendance Policy:
Regular attendance is essential for satisfactory completion of this course. If you have excessive absences, you cannot develop to your fullest potential in the course. Students who, because of excessive absences, cannot complete the course successfully. If a student stops attending after midterm, it is the student’s responsibility to withdraw to avoid an
“F1”. The student is responsible for all assignments, changes in assignments, or other verbal information given in the class, whether in attendance or not.
Course Outline (Tentative) WEEK 1 Propositional Logic WEEK 2 Predicate Logic WEEK 3 Proof Techniques WEEK 4 Sets and Functions
WEEK 5 Sequences and Summations
WEEK 6 Algorithms and complexity analysis WEEK 7 Mid-term Exam 1
WEEK 8 Integers, divisibility, and matrices WEEK 9 Induction and recursion
WEEK 10 Counting, pigeonhole principle, permutation, and combination WEEK 11 Discrete probability
WEEK 12 Mid-term Exam 2 WEEK 13 Recurrences WEEK 14 Relations WEEK 15 Graphs
