Wierd sum of squares compilation to a single vector norm

In summary, the conversation discusses a function S(x) and its transformation into a single square. The authors describe it as || A + B || ^2, where A and B are vectors. The nature of A + B is a vector and its entries are the squares of a group of numbers. The vector is equal to the norm of a vector with those numbers as its entries. The conversation also mentions a more complicated version of the problem and how (A + B) can be represented as || (F(x) - M(x), 0) + (∂M/∂x, K).x ||^2, where the dimension of the matrix (∂M/∂x, K) is 3*4.
  • #1
Sorento7
16
0
I've encountered a function like this:
S(x) = [M(x) - F(x)] ^2 + || G(x) || ^ 2X being a 3*1 vector
M and F: vector----->scalar
G: vector------->vector and || G || meaning its norm

To change S(x) into a single square, authors have described it like this:

S(x) = || A + B || ^ 2 where A=(M(x) - F(x) , 0) and B=(0 , G(x))

I don't understand how two vectors could be added actually resulting a vector with the first eigenvalue being scalar and the second eigenvalue a 3*1 vector itself?
i.e. what is the "nature" of A + B? a vector?
 
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  • #2
Why are you describing the entries of the vector as eigenvalues?

All that they are doing is this. Suppose that
[tex] G(x)=(G_1(x),...,G_m(x))[/tex]
where each Gi takes a vector to a scalar. Then
[tex] S(x) = (M(x)-F(x))^2+G_1(x)^2+...+G_m(x)^2[/tex]
We are adding the squares of a bunch of numbers together. This is the same as taking the norm of a vector which has those numbers as its entries
[tex] S(x) = ||\left( M(x)-F(x),G_1(x),...,G_m(x) \right) ||^2 [/tex]

This vector whose norm we are taking is equal to A+B in your post
 
  • #3


Thanks this sheds some light. Forgive my rudimentary mistakes since I am actually a doctor!

Well, the problem was more complicated than I described:

A(x) = (F(x) - M(x) + ∂M/∂x * x )2 taking 3*1 vector x to scalar
B(x) = || K.x ||2 k:3*3 matrix

I am confused how can (A + B) be represented as :

|| (F(x) - M(x) , 0) + (∂M/∂x , K).x ||2

Especially, what would be the dimension of the matrix (∂M/∂x , K) ? (discrepancy between the first 1 * 3 entry and second 3 * 3?)
 

Related to Wierd sum of squares compilation to a single vector norm

1. What is a Wierd sum of squares compilation?

A Wierd sum of squares compilation is a mathematical concept where the squares of a set of numbers are added together to create a new number. This compilation can be done in various ways, resulting in different outcomes.

2. How is a single vector norm related to Wierd sum of squares compilation?

A single vector norm is a measure of the magnitude of a vector in a given space. It is related to Wierd sum of squares compilation because the norm can be calculated by taking the square root of the sum of squares of the vector's components.

3. Why is Wierd sum of squares compilation useful in science?

Wierd sum of squares compilation has various applications in science, particularly in statistics and data analysis. It is useful in finding the variance and standard deviation of a set of data, and can also help in identifying patterns and trends in a dataset.

4. Can Wierd sum of squares compilation be used for non-numerical data?

No, Wierd sum of squares compilation is typically used for numerical data only. It involves squaring the values, which is not possible with non-numerical data such as words or categories.

5. Are there any limitations to using Wierd sum of squares compilation?

While Wierd sum of squares compilation can be a useful tool, it also has limitations. For example, it is sensitive to outliers in a dataset and may not accurately represent the data if there are extreme values present. Additionally, it assumes that the data follows a certain distribution, which may not always be the case.

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