The notation of the norm of polynomials

In summary, the conversation is about clarifying the use of notation in a polynomial norm equation. The questioner is confused about the meaning of x_i and the responder explains that it represents the ith dimension of x, not the coefficient of x.
  • #1
td21
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Homework Statement



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Homework Equations





The Attempt at a Solution


what is x_i? is it the coefficient of x or simply add up 1-5?
i found the notation different from http://mathworld.wolfram.com/PolynomialNorm.html
so i am confused. Thx!
 

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  • #2
Basically, that middle part is equivalent to saying:

[tex]\sqrt{(x_1-x_1^2)^2 + (x_2-x_2^2)^2 + (x_3-x_3^2)^2 + (x_4-x_4^2)^2 + (x_5-x_5^2)^2}[/tex]

Is that what you were asking?
 
  • #3
Char. Limit said:
Basically, that middle part is equivalent to saying:

[tex]\sqrt{(x_1-x_1^2)^2 + (x_2-x_2^2)^2 + (x_3-x_3^2)^2 + (x_4-x_4^2)^2 + (x_5-x_5^2)^2}[/tex]

Is that what you were asking?

sorry, i know the notation. But i don't know what x_i means? coefficient of x?
 
  • #4
No, it actually means the ith dimension of x, I believe.
 

FAQ: The notation of the norm of polynomials

What is the notation used for the norm of polynomials?

The notation used for the norm of polynomials is ||p||, where p is the polynomial.

How is the norm of a polynomial calculated?

The norm of a polynomial is calculated by taking the square root of the sum of the squares of its coefficients.

What is the significance of the norm of polynomials in mathematics?

The norm of polynomials is significant in mathematics as it is used to measure the size or magnitude of a polynomial, and is also important in various mathematical applications such as optimization and approximation.

Can the norm of polynomials be negative?

No, the norm of polynomials cannot be negative as it is calculated using the absolute values of the coefficients, which are always non-negative.

Are there different types of norms for polynomials?

Yes, there are different types of norms for polynomials such as the Euclidean norm, the maximum norm, and the L1 norm, each with their own unique properties and applications.

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