PRESENTED BY Dr.U.KARUPPIAH DEPARTMENT OF MATHEMATICS

Slides:



Advertisements
Similar presentations
Vector Spaces A set V is called a vector space over a set K denoted V(K) if is an Abelian group, is a field, and For every element vV and K there exists.
Advertisements

Completeness and Expressiveness
THE WELL ORDERING PROPERTY Definition: Let B be a set of integers. An integer m is called a least element of B if m is an element of B, and for every x.
More Functions and Sets
Section Differentials Tangent Line Approximations A tangent line approximation is a process that involves using the tangent line to approximate a.
6.1 Vector Spaces-Basic Properties. Euclidean n-space Just like we have ordered pairs (n=2), and ordered triples (n=3), we also have ordered n-tuples.
5.3 Linear Independence.
1.  We have studied groups, which is an algebraic structure equipped with one binary operation. Now we shall study rings which is an algebraic structure.
Title: Functions, Limits and Continuity Prof. Dr. Nasima Akhter And Md. Masum Murshed Lecturer Department of Mathematics, R.U. 29 July, 2011, Friday Time:
CS 173, Lecture B August 27, 2015 Tandy Warnow. Proofs You want to prove that some statement A is true. You can try to prove it directly, or you can prove.
Mathematical Induction
CS 285- Discrete Mathematics
Chapter Three SEQUENCES
Department of Statistics University of Rajshahi, Bangladesh
Let X be a metric space. A subset M of X is said to be  Rare(Nowhere Dense) in X if its closure M has no interior points,  Meager(of First Category)
Properties of Groups Proposition 1: Let (G,  ) be a group. i.The inverse element of any element of G is unique. Remark: In view of i., we may use the.
Euclidean space Euclidean space is the set of all n-tuples of real numbers, formally with a number called distance assigned to every pair of its elements.
Prepared By Meri Dedania (AITS) Discrete Mathematics by Meri Dedania Assistant Professor MCA department Atmiya Institute of Technology & Science Yogidham.
Chapter 1 Logic and Proof.
Direct Proof and Counterexample IV: Division into Cases and the Quotient-Remainder Theorem For each of the following values of n and d, find integers q.
Modular Arithmetic with Applications to Cryptography
Chapter 2 Sets and Functions.
Discrete Mathematics CS 2610
Chapter 3 The Real Numbers.
The Language of Sets If S is a set, then
Functions of Complex Variable and Integral Transforms
Week 3 2. Review of inner product spaces
Chapter 5 Limits and Continuity.
Chapter 3 The Real Numbers.
Chapter 3 The Real Numbers.
Advanced Algorithms Analysis and Design
To any sequence we can assign a sequence with terms defined as
Chapter 3 The Real Numbers.
Chapter 3 The Real Numbers.
Set Topology MTH 251 Lecture # 8.
FIRST ORDER DIFFERENTIAL EQUATIONS
Sequences and Series of Functions
Homogeneous Functions; Equations with Homogeneous Coefficients
Chapter 3 The Real Numbers.
Chapter 3 The Real Numbers.
Derivative and properties of functions
Complex Variables. Complex Variables Open Disks or Neighborhoods Definition. The set of all points z which satisfy the inequality |z – z0|
Chapter 3 The Real Numbers.
Lecture 7 Functions.
CHAPTER 19 Series and Residues.
CSE 20: Discrete Mathematics for Computer Science Prof. Shachar Lovett
Asymptotic Notations Algorithms Lecture 9.
Quantum Two.
Copyright © Cengage Learning. All rights reserved.
Polyhedron Here, we derive a representation of polyhedron and see the properties of the generators. We also see how to identify the generators. The results.
Chap 3. The simplex method
Polyhedron Here, we derive a representation of polyhedron and see the properties of the generators. We also see how to identify the generators. The results.
Chapter 4 Sequences.
cse 521: design and analysis of algorithms
Linear Algebra Chapter 4 Vector Spaces.
Lecture 43 Section 10.1 Wed, Apr 6, 2005
Stability Analysis of Linear Systems
Chapter 3 The Real Numbers.
I.4 Polyhedral Theory (NW)
Embedding Metrics into Geometric Spaces
Quantum Foundations Lecture 3
Chapter 5 Limits and Continuity.
I.4 Polyhedral Theory.
Advanced Analysis of Algorithms
Rayat Shikshan Sanstha’s S.M.Joshi College, Hadapsar -28
5.2-Inequalities and Triangles
RAYAT SHIKSHAN SANSTHA’S S.M.JOSHI COLLEGE HADAPSAR, PUNE
THE WELL ORDERING PROPERTY
Hierarchical Routing in Networks with Bounded Doubling Dimension
Matrix Algebra THE INVERSE OF A MATRIX © 2012 Pearson Education, Inc.
Presentation transcript:

PRESENTED BY Dr.U.KARUPPIAH DEPARTMENT OF MATHEMATICS REAL ANALYSIS PRESENTED BY Dr.U.KARUPPIAH DEPARTMENT OF MATHEMATICS

METRIC SPACE DEFINITION:METRIC Let X be a non empty set. Define d:X ×X→ℝ. Then d is said to be a metric on X if it satisfies the following conditions Non negativity: d(x,y) ≥ 0 for all x, y ∈𝑋 Definiteness: d(x, y)=0 iff x=y Symmetry: d(x,y) = d(y,x) Triangle inequality: d(x,y) ≤ d(x,z) + d(z,y) for all x, y, z ∈ X

DEFINITION: METRIC SPACE A non empty set X along with the metric d on X is called Metric space. It is denoted by (X, d) or simply X. Example: Let X = ℝ. Define d: ℝ×ℝ→ℝ by d(x, y)=|x – y | for all x , y ∈ℝ To check: d is a metric on ℝ. Non negativity: d(x,y) = |x – y | ≥ 0 Definiteness: d(x, y) = 0 ⇔ |x – y | =0 ⇔ x – y =0 ⇔ x = y

Symmetry: d(x, y) = |x – y | = | -(y – x)| = |y- x | = d(y , x) Triangle inequality: Consider d(x,y) = |x- y| =| x –z + z – y | = |(x-z) – (y-z)| = |(x-z) + (z-y)| ≤ |x-z| + |z-y| =d(x,z) + d(z,y) for all x, y, z ∈ℝ

Since d satisfies all the axioms of the metric Since d satisfies all the axioms of the metric. Hence d is the metric on ℝ called Usual Metric or Standard Metric. Definition: NEIGHBOURHOOD OF A POINT Let (X,d) be a Metric space. Let p ∈X , then a neighbourhood of a point p is a set 𝑁 𝑟 (p) defined as 𝑁 𝑟 (p) = { x ∈ X : d(x,y) < r}. The number r > 0 is called radius of 𝑁 𝑟 (p).

DEFINITION: INTERIOR POINT Let (X , d) be a metric space. Let E⊂ X. Let p ∈ E. Then p is said to be an interior point of E if there exists a neighbourhood 𝑁 𝑟 (p) such that 𝑁 𝑟 (p) ⊂ E. EXAMPLE: Let X = ℝ E = ℤ = {…, -2,-1,0,1,2, …}⊂ℝ. W.K.T Neighbourhood of x = 𝑁 𝑥 (x) = (𝑥-𝜖 ,𝑥+𝜖) For 𝜖 = 2,The neighbourhood of -1 = ( -3, 1) ⊄ ℤ. That is, we cannot find any neighbourhood of any integer which is contained in ℤ. Therefore ℤ has no interior points.

EXAMPLE OF INTERIOR POINT: Let E = (2 , 6) ⊂ℝ. All reals between 2 and 6 are interior points. DEFINITION: OPEN SET Let (X , d) be a metric space. Let E ⊂X. then E is said to be an open set if every point of E is an interior point. EXAMPLE OF OPEN SET: Let X = ℝ, with usual metric. Let E = (-1 , 5) Points of E = all reals between -1 and 5 Interior point of E = all reals between -1 and 5 Therefore E is open. In General, Every open interval is open.

Let E = (0, 5) ⋃ {7} ⊂ℝ Points of E = all reals between 0 and 5, 7 Interior points of E = all reals between 0 and 5. Therefore E is not open. Let E = [1 , 5]⊂ℝ Points of E = 1, 5 and all reals between 1 and 5 Interior points of E = all reals between 1 and 5.

Theorem: Every neighbourhood is an open set Theorem: Every neighbourhood is an open set. Proof: Let (X , d) be a Metric space. Let p ∈X. Let 𝑁 𝑟 (p) be an arbitrary neighbourhood of p, r > 0. To prove: 𝑁 𝑟 (p) is an open set. i.e.,to prove : Every point of 𝑁 𝑟 (p) is an interior point.

Let q ∈ 𝑁 𝑟 (p) To prove: q is an interior point of 𝑁 𝑟 (p) Let q ∈ 𝑁 𝑟 (p) To prove: q is an interior point of 𝑁 𝑟 (p) . Let d(p, q) = h (h > 0, h < r ) …………..(1) Let 𝑁 𝑟 −ℎ (q) be a neighbourhood of q. To prove: 𝑁 𝑟 −ℎ (q) ⊆ 𝑁 𝑟 (p) Let x ∈ 𝑁 𝑟 −ℎ (q) Now to prove: x ∈ 𝑁 𝑟 (p) now x ∈ 𝑁 𝑟 −ℎ (q)⇒ d(x, q) < r – h ………..(2)

Consider d(x , p) ≤ d(x , q) + d(q , p) (by triangle inequality) < r – h + h = r (by (1) & (2)) d(x , p) < r ⇒x ∈ 𝑁 𝑟 (p) Therefore we have 𝑁 𝑟 −ℎ (q) ⊆ 𝑁 𝑟 (p) i.e., there exists a neighbourhood of q which is contained in 𝑁 𝑟 (p). ⇒ q is an interior point of 𝑁 𝑟 (p).

Since q is arbitrary, every point of 𝑁 𝑟 (p) is an interior point Since q is arbitrary, every point of 𝑁 𝑟 (p) is an interior point. 𝑁 𝑟 (p) is an open set and since this is an arbitrary neighbourhood. We can say that every neighbourhood is an open set.

DEFINITION: LIMIT POINT OF A SET Let (X , d) be a metric space DEFINITION: LIMIT POINT OF A SET Let (X , d) be a metric space. Let E⊂ X. Let p ∈ X. Then p is said to be a limit point of E if every neighbourhood of p contains atleast one point of E other than p. DEFINITION: DERIVED SET The set of all limit points of E is called derived set of E. It is denoted by 𝐸 ′ .

EXAMPLE: Let E = ( -1 , 10] Limit points of E = -1,10 and all reals between -1 and 10. 𝐸 ′ = { -1,10, all reals between -1 and 10} = [ -1, 10] Let E = (1,5) ∪ {5} Limit point of E = 1,5, all reals between 1 and 5.

DEFINITION: CLOSED SET Let (X , d) be a metric space. Let E⊂ X. Then E is said to be closed set if every limit point of E is a point of E. EXAMPLE: Let E = [0 , 1] ⊂ℝ Limit points of E = 0, 1, all reals between 0 and 1. Points of E = 0, 1, all reals between 0 and 1. Therefore E is closed. In General, every closed interval is a closed set.

DEFINITION: COMPLEMENT OF A SET Let (X , d) be a metric space. Let E⊂ X. The complement of E is denoted by 𝐸 𝑐 and is defined as 𝐸 𝑐 = { 𝑥 ∈𝑋 :𝑥 ∉𝐸 } EXAMPLE: Let (ℝ , d) be a Metric space. ℝ 𝑐 = ∅ , ∅ 𝑐 = ℝ

THE RELATION BETWEEN OPEN AND CLOSED SETS Theorem: A set E is open iff its complement is closed. Proof: Necessary part: Let E be open. To prove: 𝐸 𝑐 is closed. Let p be a limit point of 𝐸 𝑐 . It is enough to show that p ∈ 𝐸 𝑐 .

Since p is a limit point of 𝐸 𝑐 , every neighbourhood of p contain at least one point of 𝐸 𝑐 other than p. ⇒ No neighbourhood of p is contained in E. ⇒ p is not an interior point of E. But E is open. ⇒ p ∉ E ⇒ p ∈ 𝐸 𝑐 Since p is arbitrary,we can say every limit point is a point of 𝐸 𝑐 . Therefore 𝐸 𝑐 is closed.

Sufficient part: Suppose 𝐸 𝑐 is closed. To prove: E is open Sufficient part: Suppose 𝐸 𝑐 is closed. To prove: E is open. Let p ∈E (arbitrary). To prove: p is an interior point of E. Since p ∈E which implies p ∉ 𝐸 𝑐 . But 𝐸 𝑐 is closed. ⇒ p is not a limit point of 𝐸 𝑐 . ⇒ there exists a neighbourhood N of p which contains no point of 𝐸 𝑐 .

Which implies that ∃ a neighbourhood N of p such that N ∩ 𝐸 𝑐 = ∅ i. e Which implies that ∃ a neighbourhood N of p such that N ∩ 𝐸 𝑐 = ∅ i.e., ∃ a neighbourhood N of p such that N ⊂ ( 𝐸 𝑐 ) 𝑐 =E ⇒∃ a neighbourhood N of p such that N ⊂ E ⇒ p is an interior point of E. Since p is arbitrary, every point of E is an interior point of E. Therefore E is open.

THANK YOU