Presentation is loading. Please wait.

Presentation is loading. Please wait.

Discrete Maths Objectives to show the connection between relations and functions, and to introduce some functions with useful, special properties 242-213,

Similar presentations


Presentation on theme: "Discrete Maths Objectives to show the connection between relations and functions, and to introduce some functions with useful, special properties 242-213,"— Presentation transcript:

1 Discrete Maths Objectives to show the connection between relations and functions, and to introduce some functions with useful, special properties 242-213, Semester 2, 2014-2015 6. Functions 1

2 1. What is a Function? A function is a special kind or relation between two sets: f : A  B 2 A f B domaincodomain All the elements in A have a single link to a value in B All the elements in A have a single link to a value in B Some elements in B may not be used. Some may be used more than once. Some elements in B may not be used. Some may be used more than once. read this as f maps A to B; it is NOT if-then read this as f maps A to B; it is NOT if-then

3 Example The function f: P  C with P = {Linda, Max, Kathy, Peter} C = {Hat Yai, NY, Hong Kong, Bangkok} Usual function notation: f(Linda) = Hat Yai f(Max) = Hat Yai f(Kathy) = Hong Kong f(Peter) = Bangkok 3 Linda Max Kathy Peter Bangkok Hong Kong NY Hat Yai P C f

4 The range is the set of elements in B used by the function f. 4 the range Range A f B

5 2. Functions with Special Properties Function Image One-to-one Function (injective) Onto Function (surjective) One-to-one Correspondence (bijective) Identity Function Inverse Function 5

6 2.1. Function Image, f(S) 6 A f B For some subset of A (e.g. S), the set of f() values in B are its Function Image f(S). For some subset of A (e.g. S), the set of f() values in B are its Function Image f(S). S  A f(S)

7 2.2. One-to-one Function 7 also called injective also called injective A f B Each value in A maps to one value in B. Don’t need to use all the B values.

8 Examples 8 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

9 2.3. Onto Function 9 also called surjective also called surjective A f B Every element in B is linked to from A. Some elements in B may be used more than once.

10 2.4. One-to-one Correspondence 10 also called bijective also called bijective A f B Each value in A maps to one value in B and every element in B is linked to from A. Each value in A maps to one value in B and every element in B is linked to from A. bijective == injective + surjective

11 Is f injective? No Is f surjective? No Is f bijective? No. 11 Example 1 Linda Max Kathy Peter Boston New York Hong Kong Moscow f injective: 1-1; not all B surjective: all B bijective 1-1; all B injective: 1-1; not all B surjective: all B bijective 1-1; all B

12 Is f injective? No Is f surjective? Yes Is f bijective? No 12 Example 2 Linda Max Kathy Peter Boston New York Hong Kong Moscow f Paul injective: 1-1; not all B surjective: all B bijective 1-1; all B injective: 1-1; not all B surjective: all B bijective 1-1; all B

13 Is f injective? Yes Is f surjective? No Is f bijective? No 13 Example 3 injective: 1-1; not all B surjective: all B bijective 1-1; all B injective: 1-1; not all B surjective: all B bijective 1-1; all B Linda Max Kathy Peter Boston New York Hong Kong Moscow f Lubeck

14 Is f injective? No! f is not even a function 14 Example 4 injective: 1-1; not all B surjective: all B bijective 1-1; all B injective: 1-1; not all B surjective: all B bijective 1-1; all B Linda Max Kathy Peter Boston New York Hong Kong Moscow f Lubeck

15 Is f injective? Yes Is f surjective? Yes Is f bijective? Yes 15 Example 5 injective: 1-1; not all B surjective: all B bijective 1-1; all B injective: 1-1; not all B surjective: all B bijective 1-1; all B Linda Max Kathy Peter Boston New York Hong Kong Moscow f Lubeck bijective == injective + surjective Paul

16 2.5. Identity Function f : X  X is called the identity function (I x ) if every element in X is mapped to the same element e.g. 16 1 2 3 4 : Z+ 1 2 3 4 : f(x) = x * 1 f

17 2.6. Inverse Function 17 Linda Max Kathy Peter Boston New York Hong Kong Moscow f Lubeck Paul Linda Max Kathy Peter Boston New York Hong Kong Moscow f -1 Lubeck Paul example 5 If f is bijective then we can create an inverse function, f -1 if f(x) = y then f -1 (y) = x

18 18 f(Linda) = Moscow f(Max) = Boston f(Kathy) = Hong Kong f(Peter) = Lübeck f(Paul) = New York f -1 (Moscow) = Linda f -1 (Boston) = Max f -1 (Hong Kong) = Kathy f -1 (Lübeck) = Peter f -1 (New York) = Paul Inversion is only possible for bijective functions.

19 3. Composition of Functions if g: X  Y and f: Y  Z then f  g: X  Z read  as “first do g then do f” The composition of f and g is defined as: (f  g)(x) = f( g(x) ) this is why f and g are ordered this way 19

20 Diagram f  g is only possible if the range of g is a subset of the domain of f 20 X Y Z g f f  g f’s domain g’s range

21 Example f(x) = 7  x – 4, g(x) = 3  x (f  g)(5) = f( g(5) ) = f(15) = 105 – 4 = 101 In general: (f  g)(x) = f( g(x) ) = f(3  x) = 21  x - 4 21

22 Composition and Inverse (f -1 ○ f)(x) = f -1 (f(x)) = x The composition of a function and its inverse is the identity function i x 22

23 4. More Information Discrete Mathematics and its Applications Kenneth H. Rosen McGraw Hill, 2007, 7th edition chapter 2, section 2.3 23


Download ppt "Discrete Maths Objectives to show the connection between relations and functions, and to introduce some functions with useful, special properties 242-213,"

Similar presentations


Ads by Google