Q1- Define dA : X → R by dA(x) = inf{d(x,y) : y ∈ A}.
Prove that dA is bounded and uniformly continuous. Moreover, show that for all x,y ∈ X, |dA(x) − dA(y)| ≤ d(x, y).
The function dA measures how close is the point x from A. Now, Let Aε ={x∈X :dA(x)<ε}. We refer to Aε as the ε-neighborhood of A. For every finite partition γ of X and every ε > 0, let γ(ε) = ? Aε × Aε. A∈γ   Q2- Let (X, d) be a metric space. Define dˆ : X × X → R, by: ˆ
d(x, y) = min{1, d(x, y)}. (a) Prove that dˆ is a bounded metric on X. (b) Use part (a) to prove that for ε > 0 there exists a bounded metric dˆ on X such that for all ˆ
x,y∈X we have d(x,y)<1⇒d(x,y)<ε.

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
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Q1- Define dA : X → R by

dA(x) = inf{d(x,y) : y ∈ A}.
Prove that dA is bounded and uniformly continuous. Moreover, show

that for all x,y ∈ X,

|dA(x) − dA(y)| ≤ d(x, y).
The function dA measures how close is the point x from A. Now, Let

Aε ={x∈X :dA(x)<ε}. We refer to Aε as the ε-neighborhood of A.

For every finite partition γ of X and every ε > 0, let γ(ε) = ? Aε × Aε.

A∈γ

 

Q2- Let (X, d) be a metric space. Define dˆ : X × X → R, by:

ˆ
d(x, y) = min{1, d(x, y)}.

(a) Prove that dˆ is a bounded metric on X. (b) Use part (a) to prove that for ε > 0 there exists a bounded metric dˆ on X such that for all

ˆ
x,y∈X we have d(x,y)<1⇒d(x,y)<ε.

 

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