Prove Least Squares Equation Has Solution

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Homework Help Overview

The discussion revolves around proving that the least squares equation, represented as A^T A x^* = A^T b, always has a solution. The context is within linear algebra, specifically focusing on the least squares method used for approximating solutions to overdetermined systems.

Discussion Character

  • Exploratory, Assumption checking, Conceptual clarification

Approaches and Questions Raised

  • Participants explore two scenarios regarding the invertibility of A^T A, discussing implications for finding a solution. There are attempts to clarify the conditions under which a unique solution might be required, including considerations of minimum norm solutions and the use of pseudo-inverses.

Discussion Status

The discussion is ongoing, with participants questioning how to demonstrate that A^T b lies within the column space of A^T A. Some guidance has been offered regarding the use of pseudo-inverses and singular value decomposition, but no consensus has been reached on the proof itself.

Contextual Notes

Participants note that the original question does not explicitly require a unique solution, which may affect the approach to proving the existence of a solution in the non-invertible case.

dirk_mec1
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Homework Statement



In the least squares method the vector x* that is the best approximation to b statisfies the Least squares equation:

[tex]A^T A x^*= A^T b[/tex]

Prove that there's always a solution to this equation.

Homework Equations


-

The Attempt at a Solution


I distinct 2 situations [tex]A^T A[/tex] is invertible and it isn't invertible. If it's invertible then there's no problem [tex]x^*= (A^T A)^{-1} A^T b[/tex]

But how I prove that it works in the non-invertible case?
 
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dirk_mec1 said:

Homework Statement



In the least squares method the vector x* that is the best approximation to b statisfies the Least squares equation:

[tex]A^T A x^*= A^T b[/tex]

Prove that there's always a solution to this equation.

Homework Equations

The Attempt at a Solution


I distinct 2 situations [tex]A^T A[/tex] is invertible and it isn't invertible. If it's invertible then there's no problem [tex]x^*= (A^T A)^{-1} A^T b[/tex]

But how I prove that it works in the non-invertible case?

If it is not invertible you need another criteria to get a unique solution. For instance you could require that x has minimum norm. In which case use could use the pseudo inverse which is based on singular value decomposition. However, you do not required a unique solution in the above question. So perhaps you could try showing that the columns of A^T form the same column space as the columns of A^TA.
 
John Creighto said:
If it is not invertible you need another criteria to get a unique solution. For instance you could require that x has minimum norm. In which case use could use the pseudo inverse which is based on singular value decomposition. However, you do not required a unique solution in the above question. So perhaps you could try showing that the columns of A^T form the same column space as the columns of A^TA.

Don't you mean the columns of [tex]A^T b[/tex] are in the span of the columns of [tex]A^T A[/tex]? If so I don't understand how to prove such a thing.
 
I've thought about it and I seriously don't know how to prove that the A^Tb is in the column space of A^TA. Can someone help me?
 

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