1 / 18

Theory of Computing

Theory of Computing. Topics Formal languages automata computability and related matters. Purposes To know the foundations and principles of computer science To learn the material that is useful in subsequent course. Prerequisites Fundamentals of data structures and algorithms

alexia
Download Presentation

Theory of Computing

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Theory of Computing Topics • Formal languages • automata • computability and related matters Purposes • To know the foundations and principles of computer science • To learn the material that is useful in subsequent course Prerequisites • Fundamentals of data structures and algorithms • Discrete mathematics that includes set, functions, relations, logic, and mathematical reasoning

  2. Example 1 The set ofpositive integers less than 100 can be denoted as Example 2 A set can also consists of seemingly unrelated elements: Chapter 1 Introduction to The Theory of Computation 1.1.1Sets Definition 1. A set is a group of objects.The objects in a set are called the elements, or members, of the set. Definition 2. Two sets are equal if and only if they have the same elements.

  3. Example 5 Draw a Venn diagram that presents V, the set of vowels in English alphabet. U a,e,i,o,u V • A set can be described by using a set builder notation. • A set can be described by using a Venn diagram.

  4. The set that has no elements is called empty set, denoted by . Definition 3. The set A is said to be a subset of B if and only if every element of A is also an element of B. We use the notation to indicate that A is a subset of the set B. U A B

  5. Definition 4. The power set of a set S is the set of all subsets of S, denoted by P(S) or . • Set Operations:

  6. U A U U U A B A B B

  7. Set Identities Table 1 Set Identities Identity Name Identity laws Domination laws Idempotent laws Complementation laws Commutative laws Associative laws Distributive laws De Morgan’s law

  8. Definition 1. Let A and B be sets. A function f from A to 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. x x y Example 1 Let set A={Adams, Chou, Goodfriend, Rodriguez, Stevens} and B={A,B,C,D,F}. Let G be the function that assigns a grade to a student in our theory of computation. z A function Not a function Adames Chou Goodfriend Rodriguez Stevens A B C D F G 1.1.2 Functions and Relations The domain of G is the set A={Adams, Chou, Goodfriend, Rodriguez, Stevens}, and the range of G is the set {A,B,C,F}.

  9. Considering the function whose domain and range are in the set of integers. We are often interested only in the behavior of these functions as their arguments become very large. Example 2

  10. Example 3 Let A={1,2,3,4}. R={(1,2), (2,3),(3,1),(4,4)} is a relation from A to A, and it is also a function from A to A. Example 4 R={(1,2), (2,3),(1,3),(1,4)} is a relation but not a function. Example 5 Let A be the set of students in the TSU. Let B the set of courses. The set R that consists of those pairs (a,b), where a is a student enrolled in course b, is a relation from A to B. Definition 3 Let A and B be the sets. A relation R from A to B is a subset of . • Functions can be consider as relations,but relations are more general than functions.

  11. Definition 4 R is an equivalence relation if for any pair (x,y) of R xRx for all x (reflexivity) If xRy then yRx (symmetry) If xRy and yRz, then xRz. (transitivity) We usually use to denote equivalence relation. Example 7 ‘=’ on the set of integers is an equivalence relation.

  12. Definition 4 R is an equivalence relation if for any pair (x,y) of R xRx for all x (reflexivity) If xRy then yRx (symmetry) If xRy and yRz, then xRz. (transitivity) We usually use to denote equivalence relation. Example 7 ‘=’ on the set of integers is an equivalence relation.

  13. Example 2 Example 1 v3 v3 e3 e3 e1 e1 v2 v2 e7 e7 e8 e8 v7 v7 v1 v1 e10 e10 e4 e4 e6 e6 v8 v8 v5 v5 e5 e5 e9 e9 v4 v4 v9 v9 e2 e2 An undirected graph A directed graph (digraph) 1.1.3 Graphs and Trees

  14. Example 3 v3 e3 e1 v2 e7 e8 v7 v1 e10 e4 e6 v8 v5 e5 e9 v4 v9 e2

  15. root Level 0 v1 Parent of v6 Level 1 v2 v4 v3 Height=3 Level 2 v8 v5 v6 Child of v3 Level 3 v7 v9 Definition 3 A tree is a directed graph that has no cycles. There is a one distinct vertex in tree, called the root.

  16. 1.1.4 A Proof Technique—Mathematical Induction

More Related