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CS 215-3
Discrete Mathematics

Catalog Description

Introduction to topics from discrete mathematics relevant to the study of computer science including: binary and hexadecimal number systems, sets, logic and truth tables, functions and relations, matrix operations, combinations, permutations, counting techniques, recurrence relations, boolean algebra, simple combinational circuits, simplification techniques.

Prerequisite:

Mathematics 111 or equivalent with a grade of C or better.

Objectives

1. To lay the mathematical foundation for further study in computer science.
2. To have the students develop a greater proficiency in basic mathematical concepts that are important in computer science at an early stage in their undergraduate education.
3. To treat these fundamental topics early in the computer science curriculum so they can be presupposed in subsequent courses.
4. To show where and how these fundamental topics impact the study of computer science. The relevance of the topics to computer science will be discussed through examples from various areas of computer science.

Organization

The course meets for three lecture hours per week. Topic coverage is given in terms of lecture hours. The following course outline is not necessarily intended as a sequential ordering. There will be at least five projects during the course of the semester. A final project that will be presented could be a group project.

Course Outline

The following is not necessarily intended as a sequential ordering. Lectures
1. Logic
Propositional logic, truth tables
Conjunction, disjunction, negation
Conditional, inverse, converse, contrapositive
Logical equivalence
Quantification: existential and universal, nesting
Counterexample
Methods of proof: direct, indirect, contradiction
Example: Logic Programming
6
2. Sets
Definitions: equality, subset, cardinality, power set
n-tuple, Cartesian product, empty set,
disjoint sets, universe
Operations: union, intersection, difference, complement
Principle of inclusion-exclusion
Set identities
Example: Computer representation of sets
2
3. Functions and relations
Definitions: function, one-to-one functions, onto functions, domain range, inverse function, composition
Representing the graph of a function
Common functions: floor, ceiling, factorial, absolute value, polynomial functions
Horner's method
Properties of relations: reflexive, symmetric, transitive, composite of two relations
Equivalence relations
Equivalence classes and partitions
n-ary relations
Examples: Growth curves, databases and relations
4
4. Integers
Definition of division
Definition of a prime number and a composite
Fundamental theorem of arithmetic
Prime factorizations
The division algorithm
Concept of the div and mod operators
Greatest common divisor
Least common multiple
Modular arithmetic
Representations of integers in decimal, binary, and hexadecimal
Conversion from one base to another
Horner's method
Euclidean algorithm
Examples: Pseudo random numbers, cryptography
4
5. Matrices
Definitions: identity matrix, sum, product, transpose symmetric matrix
Example: Representation of relations using matrices
2
6. Sequences and Summations
Arithmetic progression
Geometric progression
Summation notation
Common summation
2
7. Proof by Mathematical Induction
Mechanics of a proof
Validity of a proof by mathematical induction
2
8. Counting Techniques
Product rule
Sum rule
Principle of inclusion-exclusion
Use of tree diagrams
Permutations
Combinations
Binomial Theorem
Pascal's triangle
Permutations with repetitions
Example: Generating permutations and combinations
3
9. Recurrence Relations
Definitions
Common examples: compound interest, Fibonacci numbers, Tower of Hanoi
Solving recurrence relations
  • linear homogeneous relations with constant coefficients
  • linear nonhomogeneous relations with constant coefficients

  • Example: Divide and conquer recurrence relations
    3
    10. Boolean Algebra
    Boolean Algebra and Logic Gates
    Simplification of Boolean Functions
  • Karnaugh Maps

  • Simple Combinational Circuits
    12
      Total 40

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