Understanding the L2-Norm and its Equation

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SUMMARY

The L2-norm is defined as the square root of the integral of the square of the absolute value of a function. In the context of the equation E(N) = 2*pi∫(u(N) - uexact)² r dr, E represents the error for a specific N, and this equation calculates the variance of the random variable u(N) in polar coordinates. The equation indicates that u(N) is independent of angle, focusing on the radial component. Understanding this concept is crucial for applications in functional analysis and statistics.

PREREQUISITES
  • Understanding of Lp spaces, specifically for 0 ≤ p < ∞
  • Familiarity with integral calculus and polar coordinates
  • Basic knowledge of variance and error analysis in statistics
  • Experience with functions and their absolute values in mathematical contexts
NEXT STEPS
  • Study the properties of L2-norm and its applications in functional analysis
  • Learn about variance and its significance in statistical analysis
  • Explore polar coordinates and their use in multidimensional calculus
  • Read "Functional Analysis" by Walter Rudin for deeper insights into Lp spaces
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Mathematicians, statisticians, data scientists, and anyone interested in understanding error analysis and variance in mathematical functions.

mcooper
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Could someone please explain to me in fairly basic terms what the L2-norm is and what it does please. More specifically let me know what the following equation does...

E(N) = 2*pi\int(u(N) - uexact)2 r dr

Where E is the error for a specific N. I haven't found any good resources for learning about this on the internet. Also if someone could recommend a good book that would be great.

Thanks in advance.
 
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I know of l_p spaces. For 0\leq p&lt;\infty it's the set whose elements are sequences of scalars x=\{\lambda_1, \lambda_2, \ldots, \lambda_n,\ldots\} such that \left(\sum|\lambda_n|^p\right)^{\frac{1}{p}} is convergent.

But, I can't really help you with your problem.
 
Last edited:
mcooper said:
Could someone please explain to me in fairly basic terms what the L2-norm is and what it does please. More specifically let me know what the following equation does...

E(N) = 2*pi\int(u(N) - uexact)2 r dr

Where E is the error for a specific N. I haven't found any good resources for learning about this on the internet. Also if someone could recommend a good book that would be great.

Thanks in advance.
L2 norm (general) is the square root of the integral of the square of the absolute value of the function.

Your specific equation is for the variance (square of L2 norm, centered at the mean) of some random variable u(N). It looks like it is two dimensional, expressed in polar coordinates, where u(N) is independent of angle.
 

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