Troubleshooting Metric Space Problems: Infimum and Closed Sets

In summary, the conversation discusses a metric space problem involving a set S in R^n and a function f(x) defined as the infimum of the set of distances between x and y, where y is in S. The two problems presented are: (a) proving that if S is a closed set and x is not in S, then f(x) is greater than 0; and (b) proving that if S is a closed set, then S is equal to the set of x in R^n where f(x) is 0. Possible solutions are suggested, but one may not suffice as it does not use the closedness of S. The conversation ends with a request for help and a clarification on the relationship between the
  • #1
Mathman23
254
0
Hi

I have this here metric space problem which caused me some trouble:

[tex]S \subseteq \mathbb{R}^n[/tex] then the set

[tex]\{ \| x - y \| \ | y \in S \} [/tex] has the infimum [tex]f(x) = \{ \| x - y \| \ | y \in S \}[/tex]

where f is defined [tex]f: \mathbb{R}^n \rightarrow \mathbb{R}[/tex]
I have two problems here which I'm unable to solve:

(a) show, if S is a closed set and [tex]x \notin S [/tex] then [tex]f(x) > 0[/tex] ?

(b) show, if S is a closed set, then [tex]S = \{ x \in \mathbb{R}^n | f(x) = 0\}[/tex] ?

I need to hand this in tomorrow, and I have been strugling this these two problems the last week, therefore I would very much appreciate if anybody could give me an idear on how to solve the two problems above.

God bless,

Best Regards,
Fred
 
Last edited:
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  • #2
[tex]f(x) = \{ \| x - y \| \ | y \in S \}[/tex] ??

That would mean to each x in R^n, f maps x to ||x-y|| for all y in S. So as soon as card(S)>1, f is not a function.

Also, what do you mean by "[tex]\{ \| x - y \| \ | y \in S \} [/tex] has the infimum f(x)"?
 
  • #3
quasar987 said:
[tex]f(x) = \{ \| x - y \| \ | y \in S \}[/tex] ??

That would mean to each x in R^n, f maps x to ||x-y|| for all y in S. So as soon as card(S)>1, f is not a function.

Also, what do you mean by "[tex]\{ \| x - y \| \ | y \in S \} [/tex] has the infimum f(x)"?

Sorry it should have said

[tex]f(x) = \mathrm{inf} \{ \| x - y \| \ | y \in S \}[/tex]

Any idears on how to go about this?

Best Regards

Fred

p.s. My problems deals with the distance from [tex]\mathbb{R}^n[/tex] to a point in a subset S of [tex]\mathbb{R}^n[/tex].
 
Last edited:
  • #4
a) wouldn't that exeedingly simply argument suffice:

we know that ||x-y|| = 0 iff x=y. But since x is not in S, x is not equal to y for any y in S. Hence, ||x-y||>0.

There's probably a problem with this argument as it doesn't even use the closedness of S...
 
  • #5
Hello and thank You for Your answer,

Then (B) is that the oposite of (A) ??

Sincerely and God bless

Fred

quasar987 said:
a) wouldn't that exeedingly simply argument suffice:

we know that ||x-y|| = 0 iff x=y. But since x is not in S, x is not equal to y for any y in S. Hence, ||x-y||>0.

There's probably a problem with this argument as it doesn't even use the closedness of S...
 

1. What is a metric space?

A metric space is a mathematical concept that describes a set of objects and a function that measures the distance between those objects. It is an abstract space that can be used to describe the relationships between points or objects.

2. What is the HELP metric space problem?

The HELP metric space problem refers to a specific problem in the field of data analysis and machine learning, where the goal is to find a metric space that optimally represents a given dataset. This problem is often encountered in tasks such as clustering, dimensionality reduction, and data visualization.

3. How is the HELP metric space problem solved?

The HELP metric space problem is typically solved using algorithms that aim to find the optimal metric space that minimizes a given objective function. These algorithms often involve techniques such as gradient descent, convex optimization, or heuristic search.

4. What are the applications of the HELP metric space problem?

The HELP metric space problem has various applications in data analysis and machine learning. It can be used for tasks such as clustering, classification, anomaly detection, and data visualization. It also has applications in fields such as bioinformatics, natural language processing, and image analysis.

5. What are the challenges in solving the HELP metric space problem?

There are several challenges in solving the HELP metric space problem, including finding an appropriate objective function, dealing with high-dimensional datasets, and handling noisy or incomplete data. Additionally, the computation time and memory requirements can be significant, especially for large datasets.

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