Are the metrics d_infty and d_e equivalent?

In summary, the conversation discusses two metrics, d_{\infty}(x,y) and d_e(x,y), for the set of all bounded real-valued sequences, and the task is to prove that these metrics are not equivalent. The homework equations state the conditions for two distance functions to be equivalent, and the attempt at a solution involves finding a counterexample for the given sequence {x_n}. One possible counterexample is the Kronecker delta, which can be used to show that the two metrics are not equivalent.
  • #1
complexnumber
62
0

Homework Statement



Let [tex]X = \textbf{b}[/tex] denote the set of all bounded real-valued
sequences. Define the two metrics:
[tex]
\begin{align*}
d_{\infty}(x,y) := \sup_{n \in \mathbb{N}} |x_n - y_n| \text{,
and } d_e(x,y) := \sum^\infty_{n=1} \frac{1}{2^n} \frac{|x_n -
y_n|}{1 + |x_n - y_n|}
\end{align*}
[/tex]
for [tex]x = (x_1,x_2,\ldots), y = (y_1,y_2,\ldots) \in \textbf{b} = X[/tex].

Prove that these metrics are not equivalent.

Homework Equations



For a space [tex] X \ne \varnothing [/tex], two distance functions [tex]d_1,d_2[/tex] are equivalent if for all sequences [tex]\{x_k \} \subset X[/tex] [tex]\lim_{k \to \infty} d_1(x_k,x) = 0[/tex] if and only if [tex]\lim_{k \to \infty} d_2(x_k,x) = 0[/tex].

The Attempt at a Solution



I guess the proof is to show that for sequence [tex]\boldsymbol{x}^{(k)}[/tex], [tex]\lim_{k \to \infty} d_{e}(x^{(k)}, x) \ne 0[/tex] when [tex]\lim_{k \to \infty} d_{\infty}(x^{(k)}, x) = 0[/tex]. But how can I prove this? What area of math do I need?
 
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  • #2
complexnumber said:

Homework Statement



Let [tex]X = \textbf{b}[/tex] denote the set of all bounded real-valued
sequences. Define the two metrics:
[tex]
\begin{align*}
d_{\infty}(x,y) := \sup_{n \in \mathbb{N}} |x_n - y_n| \text{,
and } d_e(x,y) := \sum^\infty_{n=1} \frac{1}{2^n} \frac{|x_n -
y_n|}{1 + |x_n - y_n|}
\end{align*}
[/tex]
for [tex]x = (x_1,x_2,\ldots), y = (y_1,y_2,\ldots) \in \textbf{b} = X[/tex].

Prove that these metrics are not equivalent.

Homework Equations



For a space [tex] X \ne \varnothing [/tex], two distance functions [tex]d_1,d_2[/tex] are equivalent if for all sequences [tex]\{x_k \} \subset X[/tex] [tex]\lim_{k \to \infty} d_1(x_k,x) = 0[/tex] if and only if [tex]\lim_{k \to \infty} d_2(x_k,x) = 0[/tex].

The Attempt at a Solution



I guess the proof is to show that for sequence [tex]\boldsymbol{x}^{(k)}[/tex], [tex]\lim_{k \to \infty} d_{e}(x^{(k)}, x) \ne 0[/tex] when [tex]\lim_{k \to \infty} d_{\infty}(x^{(k)}, x) = 0[/tex]. But how can I prove this? What area of math do I need?

Think about {xn} where xn(k) = δnk, the Kronecker delta.
 
  • #3
LCKurtz said:
Think about {xn} where xn(k) = δnk, the Kronecker delta.

Thank you for the suggestion. I can see this is a very smart counter example. Do you know with this kind of questions if we are supposed to prove by contradiction or a more generic way?
 
  • #4
complexnumber said:
I guess the proof is to show that for sequence [tex]\boldsymbol{x}^{(k)}[/tex], [tex]\lim_{k \to \infty} d_{e}(x^{(k)}, x) \ne 0[/tex] when [tex]\lim_{k \to \infty} d_{\infty}(x^{(k)}, x) = 0[/tex]. But how can I prove this? What area of math do I need?

complexnumber said:
Thank you for the suggestion. I can see this is a very smart counter example. Do you know with this kind of questions if we are supposed to prove by contradiction or a more generic way?

You yourself described above what you need to do. Try it with the sequence I suggested.
 

FAQ: Are the metrics d_infty and d_e equivalent?

What are equivalent metric functions?

Equivalent metric functions are mathematical functions that measure the distance between two points in a given space. They are considered equivalent if they produce the same value for any given pair of points.

What is the significance of equivalent metric functions in science?

Equivalent metric functions are important in science because they provide a way to quantify the distance between objects or points in a given space. This is essential in many fields, such as physics, chemistry, and biology, where accurate measurements are crucial.

Can equivalent metric functions be used in any type of space?

Yes, equivalent metric functions can be used in any type of space, including Euclidean spaces, non-Euclidean spaces, and abstract spaces. The definition of metric functions remains the same regardless of the space they are applied to.

What is the difference between equivalent and non-equivalent metric functions?

The main difference between equivalent and non-equivalent metric functions is that equivalent functions produce the same value for any given pair of points, while non-equivalent functions may produce different values. Equivalent functions also satisfy certain properties, such as the triangle inequality, which non-equivalent functions may not.

How are equivalent metric functions used in real-world applications?

Equivalent metric functions have numerous real-world applications, such as in navigation systems, where they are used to calculate the distance between two locations. They are also used in data analysis, machine learning, and image recognition to measure the similarity between data points or images.

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