10/26/20151 … and the following mathematical appetizer is about… Functions.

Slides:



Advertisements
Similar presentations
© Bharati Vidyapeeth’s Institute of Computer Applications and Management, New Delhi-63, by Manish Kumar PRE. 1 Theory Of Computation Pre-requisite.
Advertisements

Functions Section 2.3 of Rosen Fall 2008
Lecture 3 Set Operations & Set Functions. Recap Set: unordered collection of objects Equal sets have the same elements Subset: elements in A are also.
CSE115/ENGR160 Discrete Mathematics 02/16/12 Ming-Hsuan Yang UC Merced 1.
Functions Goals Introduce the concept of function Introduce injective, surjective, & bijective functions.
1 Section 1.8 Functions. 2 Loose Definition Mapping of each element of one set onto some element of another set –each element of 1st set must map to something,
CS 2210 (22C:019) Discrete Structures Sets and Functions Spring 2015 Sukumar Ghosh.
February 5, 2015Applied Discrete Mathematics Week 1: Logic and Sets 1 Homework Solution PQ  (P  Q) (  P)  (  Q)  (P  Q)  (  P)  (  Q) truetruefalsefalsetrue.
Functions.
Functions. Let A and B be sets A function is a mapping from elements of A to elements of B and is a subset of AxB i.e. can be defined by a set of tuples!
Section 1.8: Functions A function is a mapping from one set to another that satisfies certain properties. We will first introduce the notion of a mapping.
Functions.
Sets Set Operations Functions. 1. Sets 1.1 Introduction and Notation 1.2 Cardinality 1.3 Power Set 1.4 Cartesian Products.
2.1 Sets 2.2 Set Operations 2.3 Functions ‒Functions ‒ Injections, Surjections and Bijections ‒ Inverse Functions ‒Composition 2.4 Sequences and Summations.
FUNCTION Discrete Mathematics Asst. Prof. Dr. Choopan Rattanapoka.
February 12, 2015Applied Discrete Mathematics Week 2: Functions and Sequences 1Exercises Question 1: Given a set A = {x, y, z} and a set B = {1, 2, 3,
Discrete Maths Objectives to show the connection between relations and functions, and to introduce some functions with useful, special properties ,
My Introduction Name: Prakash ADHIKARI Academic Qualification: Master’s Degree Research, Universite Lumiere-IUT Lumiere, Lyon - 2(ULL-2), France Master’s.
Functions. Copyright © Peter Cappello2 Definition Let D and C be nonempty sets. A function f from D to C, for each element d  D, assigns exactly 1 element.
Discrete Mathematics and Its Applications Sixth Edition By Kenneth Rosen Copyright  The McGraw-Hill Companies, Inc. Permission required for reproduction.
Fall 2002CMSC Discrete Structures1 … and the following mathematical appetizer is about… Functions.
Discrete Mathematics CS 2610 September 12, Agenda Last class Functions  Vertical line rule  Ordered pairs  Graphical representation  Predicates.
Functions Section 2.3 of Rosen Spring 2012 CSCE 235 Introduction to Discrete Structures Course web-page: cse.unl.edu/~cse235 Questions: Use Piazza.
MSU/CSE 260 Fall Functions Read Section 1.8.
Dr. Eng. Farag Elnagahy Office Phone: King ABDUL AZIZ University Faculty Of Computing and Information Technology CPCS 222.
1 Discrete Structures – CNS 2300 Text Discrete Mathematics and Its Applications (5 th Edition) Kenneth H. Rosen Chapter 1 The Foundations: Logic, Sets,
Functions1 Elementary Discrete Mathematics Jim Skon.
Chapter 1 SETS, FUNCTIONs, ELEMENTARY LOGIC & BOOLEAN ALGEBRAs BY: MISS FARAH ADIBAH ADNAN IMK.
Based on Rosen, Discrete Mathematics & Its Applications, 5e Prepared by (c) Michael P. Frank Modified by (c) Haluk Bingöl Module #4.
321 Section, Week 3 Natalie Linnell. Functions A function from A to B is an assignment of exactly one element of B to each element of A. We write f(a)
1.4 Sets Definition 1. A set is a group of objects . The objects in a set are called the elements, or members, of the set. Example 2 The set of positive.
Example Prove that: “IF 3n + 2 is odd, then n is odd” Proof by Contradiction: -p = 3n + 2 is odd, q = n is odd. -Assume that ~(p  q) is true OR -(p 
Basic Structures: Functions Muhammad Arief download dari
CSE 2353 – October 1 st 2003 Functions. For Real Numbers F: R->R –f(x) = 7x + 5 –f(x) = sin(x)
Agenda Week 10 Lecture coverage: –Functions –Types of Function –Composite function –Inverse of a function.
CompSci 102 Discrete Math for Computer Science January 31, 2012 Prof. Rodger Slides modified from Rosen AB a b c d x y z.
Functions. L62 Agenda Section 1.8: Functions Domain, co-domain, range Image, pre-image One-to-one, onto, bijective, inverse Functional composition and.
Fall 2003CMSC Discrete Structures1 … and now for something completely different… Set Theory Actually, you will see that logic and set theory are.
Basic Structures: Sets, Functions, Sequences, and Sums.
Functions Discrete Structure. L62 Functions. Basic-Terms. DEF: A function f : A  B is given by a domain set A, a codomain set B, and a rule which for.
CSC102 - Discrete Structures Functions
1 Functions CS 202 Epp section ??? Aaron Bloomfield.
FUNCTIONS COSC-1321 Discrete Structures 1. Function. Definition Let X and Y be sets. A function f from X to Y is a relation from X to Y with the property.
1 Lecture 5 Functions. 2 Functions in real applications Curve of a bridge can be described by a function Converting Celsius to Fahrenheit.
Ch02-Basic Structures: Sets, Functions, Sequences, Sums, and Matrices 1.
Section 2.3. Section Summary  Definition of a Function. o Domain, Cdomain o Image, Preimage  One-to-one (Injection), onto (Surjection), Bijection 
Chapter 2 1. Chapter Summary Sets The Language of Sets - Sec 2.1 – Lecture 8 Set Operations and Set Identities - Sec 2.2 – Lecture 9 Functions and sequences.
FUNCTIONS.
Discrete Mathematics Functions
Functions 7/7/2016COCS - Discrete Structures1. Functions A function f from a set A to a set B is an assignment of exactly one element of B to each element.
Functions Goals Introduce the concept of function
Functions Section 2.3.
Applied Discrete Mathematics Week 2: Functions and Sequences
Functions.
… and the following mathematical appetizer is about…
Functions.
Discrete Math for Computer Science CSC 281
Functions Section 2.3.
Discrete Math (2) Haiming Chen Associate Professor, PhD
Functions.
… and the following mathematical appetizer is about…
Functions CS 202 Epp section 7.1.
Functions.
Ch 5 Functions Chapter 5: Functions
… and the following mathematical appetizer is about…
Functions Rosen 6th ed., §2.3.
Applied Discrete Mathematics Week 3: Sets
Properties of Functions
Functions Section 2.3.
Presentation transcript:

10/26/20151 … and the following mathematical appetizer is about… Functions

10/26/20152 Functions A function f from a set A to a set B is an assignment of exactly one element of B to each element of A. We write f(a) = b if b is the unique element of B assigned by the function f to the element a of A. If f is a function from A to B, we write f: A  B (note: Here, “  “ has nothing to do with if… then)

10/26/20153 Functions If f:A  B, we say that A is the domain of f and B is the codomain of f. If f(a) = b, we say that b is the image of a and a is the pre-image of b. The range of f:A  B is the set of all images of elements of A. We say that f:A  B maps A to B.

10/26/20154 Functions Let us take a look at the function f:P  C with P = {Linda, Max, Kathy, Peter} C = {Boston, New York, Hong Kong, Moscow} f(Linda) = Moscow f(Max) = Boston f(Kathy) = Hong Kong f(Peter) = New York Here, the range of f is C.

10/26/20155 Functions Let us re-specify f as follows: f(Linda) = Moscow f(Max) = Boston f(Kathy) = Hong Kong f(Peter) = Boston Is f still a function? yes {Moscow, Boston, Hong Kong} What is its range?

10/26/20156 Functions Other ways to represent f: BostonPeter Hong Kong Kathy BostonMax MoscowLindaf(x)x LindaMax Kathy PeterBoston New York Hong Kong Moscow

10/26/20157 Functions If the domain of our function f is large, it is convenient to specify f with a formula, e.g.: f:R  R f(x) = 2x This leads to: f(1) = 2 f(3) = 6 f(-3) = -6 …

10/26/20158 Functions Let f 1 and f 2 be functions from A to R. Then the sum and the product of f 1 and f 2 are also functions from A to R defined by: (f 1 + f 2 )(x) = f 1 (x) + f 2 (x) (f 1 f 2 )(x) = f 1 (x) f 2 (x) Example: f 1 (x) = 3x, f 2 (x) = x + 5 (f 1 + f 2 )(x) = f 1 (x) + f 2 (x) = 3x + x + 5 = 4x + 5 (f 1 f 2 )(x) = f 1 (x) f 2 (x) = 3x (x + 5) = 3x x

10/26/20159 Functions We already know that the range of a function f:A  B is the set of all images of elements a  A. If we only regard a subset S  A, the set of all images of elements s  S is called the image of S. We denote the image of S by f(S): f(S) = {f(s) | s  S}

10/26/ Functions Let us look at the following well-known function: f(Linda) = Moscow f(Max) = Boston f(Kathy) = Hong Kong f(Peter) = Boston What is the image of S = {Linda, Max} ? f(S) = {Moscow, Boston} What is the image of S = {Max, Peter} ? f(S) = {Boston}

10/26/ Properties of Functions A function f:A  B is said to be one-to-one (or injective), if and only if  x, y  A (f(x) = f(y)  x = y) In other words: f is one-to-one if and only if it does not map two distinct elements of A onto the same element of B.

10/26/ Properties of Functions And again… f(Linda) = Moscow f(Max) = Boston f(Kathy) = Hong Kong f(Peter) = Boston Is f one-to-one? No, Max and Peter are mapped onto the same element of the image. g(Linda) = Moscow g(Max) = Boston g(Kathy) = Hong Kong g(Peter) = New York Is g one-to-one? Yes, each element is assigned a unique element of the image.

10/26/ Properties of Functions How can we prove that a function f is one-to-one? Whenever you want to prove something, first take a look at the relevant definition(s):  x, y  A (f(x) = f(y)  x = y) Example: f:R  R f(x) = x 2 Disproof by counterexample: f(3) = f(-3), but 3  -3, so f is not one-to-one.

10/26/ Properties of Functions … and yet another example: f:R  R f(x) = 3x One-to-one:  x, y  A (f(x) = f(y)  x = y) To show: f(x)  f(y) whenever x  y x  y  3x  3y  f(x)  f(y), so if x  y, then f(x)  f(y), that is, f is one-to-one.

10/26/ Properties of Functions A function f:A  B with A,B  R is called strictly increasing, if  x,y  A (x < y  f(x) < f(y)), and strictly decreasing, if  x,y  A (x f(y)). Obviously, a function that is either strictly increasing or strictly decreasing is one-to-one.

10/26/ Properties of Functions A function f:A  B is called onto, or surjective, if and only if for every element b  B there is an element a  A with f(a) = b. In other words, f is onto if and only if its range is its entire codomain. A function f: A  B is a one-to-one correspondence, or a bijection, if and only if it is both one-to-one and onto. Obviously, if f is a bijection and A and B are finite sets, then |A| = |B|.

10/26/ Properties of Functions Examples: In the following examples, we use the arrow representation to illustrate functions f:A  B. In each example, the complete sets A and B are shown.

10/26/ Properties of Functions Is f injective? No. Is f surjective? No. Is f bijective? No.LindaMax Kathy PeterBoston New York Hong Kong Moscow

10/26/ Properties of Functions Is f injective? No. Is f surjective? Yes. Is f bijective? No.LindaMax Kathy PeterBoston New York Hong Kong Moscow Paul

10/26/ Properties of Functions Is f injective? Yes. Is f surjective? No. Is f bijective? No.LindaMax Kathy PeterBoston New York Hong Kong Moscow Lübeck

10/26/ Properties of Functions Is f injective? No! f is not even a function! LindaMax Kathy PeterBoston New York Hong Kong Moscow Lübeck

10/26/ Properties of Functions Is f injective? Yes. Is f surjective? Yes. Is f bijective? Yes. Linda Max Kathy Peter Boston New York Hong Kong Moscow Lübeck Helena

10/26/ Inversion An interesting property of bijections is that they have an inverse function. The inverse function of the bijection f:A  B is the function f -1 :B  A with f -1 (b) = a whenever f(a) = b.

10/26/ Inversion Example: f(Linda) = Moscow f(Max) = Boston f(Kathy) = Hong Kong f(Peter) = Lübeck f(Helena) = New York Clearly, f is bijective. The inverse function f -1 is given by: f -1 (Moscow) = Linda f -1 (Boston) = Max f -1 (Hong Kong) = Kathy f -1 (Lübeck) = Peter f -1 (New York) = Helena Inversion is only possible for bijections (= invertible functions)

10/26/ Inversion Linda Max Kathy Peter Boston New York Hong Kong Moscow Lübeck Helenaf f -1 f -1 :C  P is no function, because it is not defined for all elements of C and assigns two images to the pre- image New York.

10/26/ Composition The composition of two functions g:A  B and f:B  C, denoted by f  g, is defined by (f  g)(a) = f(g(a)) This means that first, function g is applied to element a  A, mapping it onto an element of B, first, function g is applied to element a  A, mapping it onto an element of B, then, function f is applied to this element of B, mapping it onto an element of C. then, function f is applied to this element of B, mapping it onto an element of C. Therefore, the composite function maps from A to C. Therefore, the composite function maps from A to C.

10/26/ Composition Example: f(x) = 7x – 4, g(x) = 3x, f:R  R, g:R  R (f  g)(5) = f(g(5)) = f(15) = 105 – 4 = 101 (f  g)(x) = f(g(x)) = f(3x) = 21x - 4

10/26/ Composition Composition of a function and its inverse: (f -1  f)(x) = f -1 (f(x)) = x The composition of a function and its inverse is the identity function i(x) = x.

10/26/ Graphs The graph of a function f:A  B is the set of ordered pairs {(a, b) | a  A and f(a) = b}. The graph is a subset of A  B that can be used to visualize f in a two-dimensional coordinate system.

10/26/ Floor and Ceiling Functions The floor and ceiling functions map the real numbers onto the integers (R  Z). The floor function assigns to r  R the largest z  Z with z  r, denoted by  r . Examples:  2.3  = 2,  2  = 2,  0.5  = 0,  -3.5  = -4 The ceiling function assigns to r  R the smallest z  Z with z  r, denoted by  r . Examples:  2.3  = 3,  2  = 2,  0.5  = 1,  -3.5  = -3