Can local operator estimate be applied to subsets of Rn?

In summary, the Sobolev norm being equivalent to the L2 norm on compactly contained sets allows us to obtain the desired result for subsets U and V of Rn where V is only slightly larger than U.
  • #1
jiku1797
2
0
Say I have an invertible partial differential operator P:H1(Rn) -> L2(Rn) where H1 denotes the first order L2 Sobolev space. I know

|u|H1(Rn) ≤ |(P-z)u|L2(Rn)

for certain z. Can I somehow obtain

|u|H1(U) ≤ |(P-z)u|L2(V)

for subsets U, V of Rn where V is only "slightly" larger than U (e.g. U is compactly contained in V)?
 
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  • #2
Yes, you can obtain this result. The result follows from the fact that the Sobolev norm is equivalent to the L2 norm on compactly contained sets. This means that there exists a constant C such that |u|H1(U) ≤ C|u|L2(U) for all u in H1(U). Moreover, since P is an invertible partial differential operator, we also have |(P-z)u|L2(V) ≤ C'|(P-z)u|L2(V) for some constant C'. Combining these two inequalities gives us the desired result.
 

FAQ: Can local operator estimate be applied to subsets of Rn?

What is a local operator estimate?

A local operator estimate is a statistical method used to estimate the behavior or value of a function at a specific point based on the values of the function in the surrounding points.

How is a local operator estimate calculated?

A local operator estimate is calculated by using a weighted average of the function values in the surrounding points, with the weights determined by a chosen kernel function.

What is the purpose of using a local operator estimate?

The purpose of using a local operator estimate is to approximate the behavior of a function at a specific point without having to know the exact mathematical form of the function. It is commonly used in data analysis and prediction tasks.

What types of data can a local operator estimate be applied to?

A local operator estimate can be applied to any type of data that can be represented as a function, such as numerical data, time series data, and spatial data.

What are the advantages and disadvantages of using a local operator estimate?

The advantages of using a local operator estimate include its ability to handle complex and nonlinear functions, as well as its flexibility in choosing different kernel functions. However, a disadvantage is that it can be sensitive to the choice of kernel and the number of surrounding points used in the calculation.

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