Confused on definition of projection

In summary, the textbook defines a linear operator ##T## as a projection on ##W_1## along ##W_2## if, for all ##x = x_1 + x_2## with ##x_1 \in W_1## and ##x_2 \in W_2##, we have ##T(x) = x_1##. It also states that a linear operator ##T## is a projection if and only if ##T^2 = T##. However, in the case of the identity operator ##I##, it is not a projection according to the first definition, but it is a projection according to the second definition. This discrepancy is due to the fact that the second definition is
  • #1
JonnyG
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My textbook says: "if ## V = W_1 \oplus W_2 ##,, then a linear operator ## T ## on ##V ## is the projection on ##W_1## along ##W_2## if, whenever ## x = x_1 + x_2##, with ##x_1 \in W_1## and ##x_2 \in W_2##, we have ##T(x) = x_1##"

It then goes on to say that "##T## is a projection if and only ##T^2 = T##.

But what if ##T = I## (the identity operator)? Then suppose ##V## is finite dimensional and ##W## is a subspace of ##V##. Then ##V = W \oplus W^{\perp}## so that any ##x \in V## has the form ##x = x_1 + x_2##. So by the first definition, ##I## is not a projection because ##I(x) = x = x_1 + x_2 \neq x_1 ##. But by the second definition, ##I## is a projection, because ##I^2 = I##.

What's going on here?
 
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  • #2
Are you sure the second statement is a definition ... could it be a consequence of applying the definition in a particular situation.
 
  • #3
The exact wording in the book is "In fact, it can be shown (see Exercise 17 of Section 2.3) that ##T## is a projection if and only ##T^2 = T##. The article on Wikipedia also gives this definition.
 
  • #4
Id is a trivial projection, based on the trivial decomposition of V into the sum of V and the zero subspace. note: Vperp = {0}. I.e. x1+x2 = x1 precisely when x2 =0.
 
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Related to Confused on definition of projection

1. What is the definition of projection in scientific terms?

Projection is the process of transforming data from one coordinate system to another. It involves converting the 3D spatial information of an object into a 2D representation.

2. How is projection used in scientific research?

Projection is commonly used in various fields of science such as geography, cartography, and remote sensing. It allows researchers to accurately represent and analyze spatial data on maps and in other visualizations.

3. What are the different types of projection?

There are several types of projection, including cylindrical, conic, and azimuthal. Each type has its own unique properties and is suitable for different purposes. Some common projections used in scientific research include the Mercator, Robinson, and Lambert conformal conic projections.

4. What is the difference between projection and re-projection?

Projection refers to the initial transformation of data from one coordinate system to another. Re-projection, on the other hand, is the process of converting data from an existing projection to a different one. This may be necessary when combining data from different sources or creating a more accurate representation of a specific region.

5. How does projection affect the accuracy of scientific data?

The choice of projection can greatly impact the accuracy of scientific data. Some projections may distort certain areas or features, making them less accurate. It is important for scientists to carefully consider and select the most appropriate projection for their research to ensure the accuracy of their findings.

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