2-norm of a projector is greater than 1

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In summary, using the formula for the 2-norm of a projection matrix and the fact that P=P* and P^2=P, we can prove that ||P||_2 >= 1 with equality if and only if P is an orthogonal projector. This is because, for a non-zero projection matrix P, there exists a vector v such that Pv = v, and using this fact along with the definition of the 2-norm, the inequality follows.
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Let [tex]P \in \textbf{C}^{m\times m}[/tex] be a projector. We prove that [tex]\left\| P \right\| _{2}\geq 1[/tex] , with equality if and only if P is an orthogonal projector.I suppose we could use the formula [tex]\left\| P \right\| _{2}= max_{\left\| x \right\| _ {2} =1} \left\| Px \right\| _{2}[/tex] and use the fact that [tex]P^{2}=P[/tex] and [tex]P=P^{*}[/tex] (P* is the transpose conjugate of P).

But I am not sure how to use these.
 
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Technically this isn't true since [itex]P = 0[/itex] is a projection matrix with [itex]||P||_2 = 0[/itex]. But assuming [itex]P \neq 0[/itex], there exists some [itex]v \neq 0[/itex] such that

[tex]Pv = v[/tex]

If you use this fact along with the definition of the 2-norm of a matrix, your inequality follows pretty much immediately.
 

FAQ: 2-norm of a projector is greater than 1

What is a 2-norm of a projector?

The 2-norm of a projector is a mathematical concept used to measure the size or magnitude of a projector. It is calculated by taking the square root of the sum of the squared absolute values of the eigenvalues of the projector.

How is the 2-norm of a projector different from other norms?

The 2-norm of a projector is a specific type of norm, known as the spectral norm. Unlike other norms, it takes into account the eigenvalues of the projector and is used to measure the maximum amount of stretching or shrinking that the projector can cause on a vector.

Why is it important for the 2-norm of a projector to be greater than 1?

The 2-norm of a projector being greater than 1 indicates that the projector has a non-trivial effect on vectors. This is important in linear algebra and scientific computing, as it allows us to determine the stability and accuracy of numerical methods that use projectors.

In what situations would the 2-norm of a projector be less than 1?

The 2-norm of a projector can be less than 1 for projectors that are close to the identity matrix, meaning they have a minimal effect on vectors. This can occur when the projector is nearly orthogonal or when the eigenvalues of the projector are close to 1.

How is the 2-norm of a projector used in real-world applications?

The 2-norm of a projector is used in a variety of real-world applications, including image and signal processing, data compression, and machine learning. It is also used in numerical methods for solving linear systems of equations, where it helps determine the convergence and accuracy of the solution.

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