MATH-331 Discrete Mathematics Fall 2009 1. Organizational Details Class Meeting: 11 :00am-12:15pm; Monday, Wednesday; Room SCIT215 Instructor: Dr. Igor.

Slides:



Advertisements
Similar presentations
Lecture 1 RMIT University, Taylor's University Learning Objectives
Advertisements

Basic Structures: Sets, Functions, Sequences, Sums, and Matrices
Instructor: Hayk Melikya
Basic Structures: Sets, Functions, Sequences, Sums, and Matrices
Week 21 Basic Set Theory A set is a collection of elements. Use capital letters, A, B, C to denotes sets and small letters a 1, a 2, … to denote the elements.
Denoting the beginning
SET.   A set is a collection of elements.   Sets are usually denoted by capital letters A, B, Ω, etc.   Elements are usually denoted by lower case.
Sets 1.
Sets 1.
Set Theory.
1 Learning Objectives for Section 7.2 Sets After today’s lesson, you should be able to Identify and use set properties and set notation. Perform set operations.
Mathematics.
Survey of Mathematical Ideas Math 100 Chapter 2
Operations on Sets – Page 1CSCI 1900 – Discrete Structures CSCI 1900 Discrete Structures Operations on Sets Reading: Kolman, Section 1.2.
Set Notation.
This section will discuss the symbolism and concepts of set theory
CIS-305: Data Structures Fall Organizational Details Class Meeting: 4 :00-6:45pm, Tuesday, Room SCIT215 Instructor: Dr. Igor Aizenberg Office:
Set theory Sets: Powerful tool in computer science to solve real world problems. A set is a collection of distinct objects called elements. Traditionally,
Partially borrowed from Florida State University
Set Theory. What is a set?  Sets are used to define the concepts of relations and functions. The study of geometry, sequences, probability, etc. requires.
Chapter 3 – Set Theory  .
Set, Combinatorics, Probability & Number Theory Mathematical Structures for Computer Science Chapter 3 Copyright © 2006 W.H. Freeman & Co.MSCS Slides Set,
CS 103 Discrete Structures Lecture 10 Basic Structures: Sets (1)
Chapter 7 Logic, Sets, and Counting Section 2 Sets.
1 ENM 503 Block 1 Algebraic Systems Lesson 2 – The Algebra of Sets The Essence of Sets What are they?
Set Theory Dr. Ahmed Elmoasry. Contents Ch I: Experiments, Models, and Probabilities. Ch II: Discrete Random Variables Ch III: Discrete Random Variables.
Week 11 What is Probability? Quantification of uncertainty. Mathematical model for things that occur randomly. Random – not haphazard, don’t know what.
CS201: Data Structures and Discrete Mathematics I
CompSci 102 Discrete Math for Computer Science
Sets Digital Lesson. Copyright © by Houghton Mifflin Company, Inc. All rights reserved. 2 Definition of Set A set is a collection of objects called elements.
ELEMENTARY SET THEORY.
Discrete Mathematical Structures 4 th Edition Kolman, Busby, Ross © 2000 by Prentice-Hall, Inc. ISBN
Chapter SETS DEFINITION OF SET METHODS FOR SPECIFYING SET SUBSETS VENN DIAGRAM SET IDENTITIES SET OPERATIONS.
Basic Principles (continuation) 1. A Quantitative Measure of Information As we already have realized, when a statistical experiment has n eqiuprobable.
CSNB143 – Discrete Structure Topic 1 - Set. Topic 1 - Sets Learning Outcomes – Student should be able to identify sets and its important components. –
Chapter 2 With Question/Answer Animations. Section 2.1.
Rosen 1.6, 1.7. Basic Definitions Set - Collection of objects, usually denoted by capital letter Member, element - Object in a set, usually denoted by.
Introduction to Set theory. Ways of Describing Sets.
ITD1111 Discrete Mathematics & Statistics STDTLP
Discrete Mathematics Set.
Probability theory is the branch of mathematics concerned with analysis of random phenomena. (Encyclopedia Britannica) An experiment: is any action, process.
Basic probability Sep. 16, Introduction Our formal study of probability will base on Set theory Axiomatic approach (base for all our further studies.
Set Operations Section 2.2.
Notions & Notations (2) - 1ICOM 4075 (Spring 2010) UPRM Department of Electrical and Computer Engineering University of Puerto Rico at Mayagüez Spring.
Basic Probability. Introduction Our formal study of probability will base on Set theory Axiomatic approach (base for all our further studies of probability)
Thinking Mathematically Venn Diagrams and Set Operations.
Chapter 2 1. Chapter Summary Sets (This Slide) The Language of Sets - Sec 2.1 – Lecture 8 Set Operations and Set Identities - Sec 2.2 – Lecture 9 Functions.
1.1 – SETS AND SYMBOLS. Goals SWBAT understand basic set notation and set symbols SWBAT solve simple sentences with a given domain SWBAT graph sets of.
CPCS 222 Discrete Structures I
Section 6.1 Set and Set Operations. Set: A set is a collection of objects/elements. Ex. A = {w, a, r, d} Sets are often named with capital letters. Order.
Sets, Permutations, and Combinations. Lecture 4-1: Sets Sets: Powerful tool in computer science to solve real world problems. A set is a collection of.
Dr. Ameria Eldosoky Discrete mathematics
The set of whole numbers less than 7 is {1, 2, 3, 4, 5, 6}
CHAPTER 3 SETS, BOOLEAN ALGEBRA & LOGIC CIRCUITS
CSNB 143 Discrete Mathematical Structures
Lecture 04 Set Theory Profs. Koike and Yukita
Set, Combinatorics, Probability & Number Theory
Sets Section 2.1.
What is Probability? Quantification of uncertainty.
Chapter 1 Logic and Proofs Homework 2 Given the statement “A valid password is necessary for you to log on to the campus server.” Express the statement.
CS100: Discrete structures
Set Operations Section 2.2.
Algebra 1 Section 1.1.
Discrete Mathematics R. Johnsonbaugh
Chapter 7 Logic, Sets, and Counting
Sets and Probabilistic Models
Sets and Probabilistic Models
Sets, Unions, Intersections, and Complements
Sets and Probabilistic Models
Presentation transcript:

MATH-331 Discrete Mathematics Fall

Organizational Details Class Meeting: 11 :00am-12:15pm; Monday, Wednesday; Room SCIT215 Instructor: Dr. Igor Aizenberg Office: Science and Technology Building, 104C Phone ( ) Office hours: Monday, Wednesday 10am-6pm Tuesday 11pm-3pm Class Web Page : 2

Dr. Igor Aizenberg: self-introduction MS in Mathematics from Uzhgorod National University (Ukraine), 1982 PhD in Computer Science from the Russian Academy of Sciences, Moscow (Russia), 1986 Areas of research: Artificial Neural Networks, Image Processing and Pattern Recognition About 100 journal and conference proceedings publications and one monograph book Job experience: Russian Academy of Sciences ( ); Uzhgorod National University (Ukraine, and ); Catholic University of Leuven (Belgium, ); Company “Neural Networks Technologies” (Israel, ); University of Dortmund (Germany, ); National Center of Advanced Industrial Science and Technologies (Japan, 2004); Tampere University of Technology (Finland, ); Texas A&M University-Texarkana, from March,

Text Book "Discrete Mathematics" by J. A. Dossey, A. D. Otto, L. E. Spence, and C. V. Eynden, 5th Edn., Pearson/Addison Wesley, 2006, ISBN

Control  Exams (open book, open notes): Exam 1: October 5-7, 2009 Exam 2: November 4, 2009 Exam 3: December 14, 2009  Homework 5

Grading Grading Method Homework and preparation:10% Midterm Exam 1: 30% Midterm Exam 2: 30% Final Exam: 30% Grading Scale: 90%+  A 80%+  B 70%+  C 60%+  D less than 60%  F 6

What we will study? Basic concepts of discrete mathematics, which are used in computer modeling and simulation Combinatorics Probability theory Function theory Graph theory Encoding theory Elements of Mathematical Logic 7

Sets The set, in mathematics, is any collection of objects of any nature specified according to a well-defined rule. Each object in a set is called an element (a member, a point). If x is an element of the set X, ( x belongs to X ) this is expressed by means that x does not belong to X 8

Sets Sets can be finite (the set of students in the class), infinite (the set of real numbers) or empty (null - a set of no elements). A set can be specified by either giving all its elements in braces (a small finite set) or stating the requirements for the elements belonging to the set. X={a, b, c, d} X={x : x is a student taking the “Discrete Mathematics” class} 9

Sets is the set of integer numbers is the set of rational numbers is the set of real numbers is the set of complex numbers is an empty set is a set whose single element is an empty set 10

Sets What about a set of the roots of the equation The set of the real roots is empty: The set of the complex roots is, where i is an imaginary unity 11

Subsets When every element of a set A is at the same time an element of a set B then A is a subset of B (A is contained in B): For example, 12

Subsets The sets A and B are said to be equal if they consist of exactly the same elements. That is, For instance, let the set A consists of the roots of equation What about the relationships among A, B, C ? 13

Subsets 14

Cardinality The cardinality of a finite set is the number of elements in the set. |A| is the cardinality of A. A set with the same cardinality as any subset of the set of natural numbers is called a countable set. 15

Continuum For an infinite continuous linearly ordered set, which has a property that it there is always an element between other two, we say that its cardinality is “continuum” (for example, interval [0,1], any other interval, or any line) or simply call this set continuum. 16

Universal Set A large set, which includes some useful in dealing with the specific problem smaller sets, is called the universal set (universe). It is usually denoted by U. For instance, in the previous example, the set of integer numbers can be naturally considered as the universal set. 17

Operations on Sets: Union Let U be a universal set of any arbitrary elements and contains all possible elements under consideration. The universal set may contain a number of subsets A, B, C, D, which individually are well-defined. The union (sum) of two sets A and B is the set of all those elements that belong to A or B or both: 18

Operations on Sets: Union Important property: 19

Operations on Sets: Intersection The intersection (product) of two sets A and B is the set of all those elements that belong to both A and B (that are common for these sets): When the sets A and B are said to be mutually exclusive or disjoint. 20

Operations on Sets: Intersection Important property: 21

Operations on Sets: Difference The difference of two sets A and B is the set of all those elements that belong to the set A but do not belong to the set B: 22

Operations on Sets: Complement The complement (negation) of any set A is the set A’ ( ) containing all elements of the universe that are not elements of A. 23

Venn Diagrams A Venn diagram is a useful mean for representing relationships among sets (see p. 44 in the text book). In a Venn diagram, the universal set is represented by a rectangular region, and subsets of the universal set are represented by circular discs drawn within the rectangular region. 24

Algebra of Sets Let A, B, and C be subsets of a universal set U. Then the following laws hold. Commutative Laws: Associative Laws: Distributive Laws: 25

Algebra of Sets Complementary: Difference Laws: 26

Algebra of Sets De Morgan’s Laws (Dualization): Involution Law: Idempotent Law: For any set A: 27