Are the Weak and Strong Norms Correct for These Function Distances?

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In summary: If your definitions of the weak and strong norms are correct then so are those answers. But the definitions look odd to me because the "weak" norm is stronger than the "strong" norm. :confused:Do you have a source that you can reference that defines the norms more accurately?
  • #1
evinda
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Hello! (Wave)

In $C^1[0,1]$ calculate the distances between the functions $y_1(x)=0$ and $y_2(x)=\frac{1}{100} \sin(1000x)$ in respect to the weak and strong norm.That's what I have tried:Weak norm:

$||y_1-y_2||_w=\max_{0 \leq x \leq 1} |y_1(x)-y_2(x)|+ \max_{0 \leq x \leq 1} |y_1'(x)-y_2'(x) | \\=\max_{0 \leq x \leq 1} \left |0-\frac{1}{100} \sin(1000x) \right|+ \max_{0 \leq x \leq 1} \left |\frac{1000}{100} \cos(1000x) \right|= \frac{1}{100}+10=\frac{1001}{100}$

Strong norm:

$||y_1-y_2||_M= \max_{0 \leq x \leq 1} |y_1(x)-y_2(x)|=\max_{0 \leq x \leq 1} \left |y_1(x)-y_2(x) \right|= \\=\max_{0 \leq x \leq 1} \left |0-\frac{1}{100} \sin(1000x) \right|= \frac{1}{100} \max_{0 \leq x \leq 1} |\sin(1000x)|= \frac{1}{100}$

Could you tell me if that what I have tried is right? (Thinking)
 
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  • #2
evinda said:
Hello! (Wave)

In $C^1[0,1]$ calculate the distances between the functions $y_1(x)=0$ and $y_2(x)=\frac{1}{100} \sin(1000x)$ in respect to the weak and strong norm.That's what I have tried:Weak norm:

$||y_1-y_2||_w=\max_{0 \leq x \leq 1} |y_1(x)-y_2(x)|+ \max_{0 \leq x \leq 1} |y_1'(x)-y_2'(x) | \\=\max_{0 \leq x \leq 1} \left |0-\frac{1}{100} \sin(1000x) \right|+ \max_{0 \leq x \leq 1} \left |\frac{1000}{100} \cos(1000x) \right|= \frac{1}{100}+10=\frac{1001}{100}$

Strong norm:

$||y_1-y_2||_M= \max_{0 \leq x \leq 1} |y_1(x)-y_2(x)|=\max_{0 \leq x \leq 1} \left |y_1(x)-y_2(x) \right|= \\=\max_{0 \leq x \leq 1} \left |0-\frac{1}{100} \sin(1000x) \right|= \frac{1}{100} \max_{0 \leq x \leq 1} |\sin(1000x)|= \frac{1}{100}$

Could you tell me if that what I have tried is right? (Thinking)
If your definitions of the weak and strong norms are correct then so are those answers. But the definitions look odd to me because the "weak" norm is stronger than the "strong" norm. :confused:
 
  • #3
Opalg said:
If your definitions of the weak and strong norms are correct then so are those answers. But the definitions look odd to me because the "weak" norm is stronger than the "strong" norm. :confused:

According to my textbook:In the linear space $C^1[a,b]$, the norm that is defined as

$$||y||_w=\max_{a \leq x \leq b} |y(x)|+ \max_{a \leq x \leq b} |y'(x)|$$

is called weak norm.

The maximum norm that we define like that: $||y||_M=\max_{a \leq x \leq b} |y(x)| dx$ is called strong norm.
 
  • #4
Opalg said:
If your definitions of the weak and strong norms are correct then so are those answers. But the definitions look odd to me because the "weak" norm is stronger than the "strong" norm. :confused:

So do you think that it is a typo? (Thinking)
 

FAQ: Are the Weak and Strong Norms Correct for These Function Distances?

What is the definition of "Distances between the functions"?

The distance between two functions is a measure of how different or similar they are. It is calculated by finding the minimum amount of change needed to transform one function into the other.

How is the distance between two functions calculated?

The most commonly used method for calculating the distance between two functions is by using the L2 norm or Euclidean distance, which involves taking the square root of the sum of the squared differences between corresponding data points.

What are some real-world applications of measuring distances between functions?

Distances between functions are used in various fields such as signal processing, data analysis, and machine learning. They are also used in image and audio recognition, pattern recognition, and similarity searching.

What are the limitations of using distances between functions?

One limitation is that the distance between functions is heavily dependent on the choice of distance metric and can vary significantly with different metrics. Additionally, distances may not accurately reflect the similarity between functions if they have different shapes or patterns.

How can distances between functions be used to compare different functions?

Distances between functions can be used to identify the most similar or dissimilar functions in a dataset. They can also be used to cluster similar functions together and to classify new functions based on their distance to existing functions.

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