Least square solution to the system











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I am trying to solve the following problem:




Let $u_1$ and $u_2$ be two orthogonal vectors in ${rm I!R}^n$ and
set $a_1 = u_1$, $a_2 = u_1 + varepsilon u_2$ for $varepsilon>0$.
Let also $A$ be the matrix with columns $a_1$ and $a_2$ and $b$ a
vector linearly independenet of $a_1$ and $a_2$. Least square solution
is discussed here to the system $Ax = b$ as $varepsilonto0$.



(a) Find the matrix $A^top A$, its inverse, and then $hat{x} =
> (A^top A)^{-1}A^top b$
explicitly. Show that $hat{x}$ explodes as
$varepsilonto0$



(b) Find the projection $Ahat{x}$ of $b$ onto $operatorname{col}(A)$
and check that it does not depend on $varepsilon>0$. Explain the
result.




I have assumed, that $A = begin{pmatrix}u_1 & u_1+varepsilon u_2end{pmatrix}$, therefore:



$A^TA=begin{pmatrix}u_1 \ u_1+varepsilon u_2end{pmatrix}begin{pmatrix}u_1 & u_1+varepsilon u_2end{pmatrix}=begin{pmatrix}u_1^2 & u_1(u_1+varepsilon u_2)\u_1(u_1+varepsilon u_2) & (u_1 + varepsilon u_2)^2end{pmatrix}$



But when I try to compute $(A^TA)^{-1}$, determinant becomes zero, what means that matrix is not invertible. What am I doing wrong? Thanks in advance for any hints!










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  • I guess that $A^T*A$ always has a zero determinant unless A is invertible.
    – NoChance
    yesterday















up vote
0
down vote

favorite












I am trying to solve the following problem:




Let $u_1$ and $u_2$ be two orthogonal vectors in ${rm I!R}^n$ and
set $a_1 = u_1$, $a_2 = u_1 + varepsilon u_2$ for $varepsilon>0$.
Let also $A$ be the matrix with columns $a_1$ and $a_2$ and $b$ a
vector linearly independenet of $a_1$ and $a_2$. Least square solution
is discussed here to the system $Ax = b$ as $varepsilonto0$.



(a) Find the matrix $A^top A$, its inverse, and then $hat{x} =
> (A^top A)^{-1}A^top b$
explicitly. Show that $hat{x}$ explodes as
$varepsilonto0$



(b) Find the projection $Ahat{x}$ of $b$ onto $operatorname{col}(A)$
and check that it does not depend on $varepsilon>0$. Explain the
result.




I have assumed, that $A = begin{pmatrix}u_1 & u_1+varepsilon u_2end{pmatrix}$, therefore:



$A^TA=begin{pmatrix}u_1 \ u_1+varepsilon u_2end{pmatrix}begin{pmatrix}u_1 & u_1+varepsilon u_2end{pmatrix}=begin{pmatrix}u_1^2 & u_1(u_1+varepsilon u_2)\u_1(u_1+varepsilon u_2) & (u_1 + varepsilon u_2)^2end{pmatrix}$



But when I try to compute $(A^TA)^{-1}$, determinant becomes zero, what means that matrix is not invertible. What am I doing wrong? Thanks in advance for any hints!










share|cite|improve this question







New contributor




Michael is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.




















  • I guess that $A^T*A$ always has a zero determinant unless A is invertible.
    – NoChance
    yesterday













up vote
0
down vote

favorite









up vote
0
down vote

favorite











I am trying to solve the following problem:




Let $u_1$ and $u_2$ be two orthogonal vectors in ${rm I!R}^n$ and
set $a_1 = u_1$, $a_2 = u_1 + varepsilon u_2$ for $varepsilon>0$.
Let also $A$ be the matrix with columns $a_1$ and $a_2$ and $b$ a
vector linearly independenet of $a_1$ and $a_2$. Least square solution
is discussed here to the system $Ax = b$ as $varepsilonto0$.



(a) Find the matrix $A^top A$, its inverse, and then $hat{x} =
> (A^top A)^{-1}A^top b$
explicitly. Show that $hat{x}$ explodes as
$varepsilonto0$



(b) Find the projection $Ahat{x}$ of $b$ onto $operatorname{col}(A)$
and check that it does not depend on $varepsilon>0$. Explain the
result.




I have assumed, that $A = begin{pmatrix}u_1 & u_1+varepsilon u_2end{pmatrix}$, therefore:



$A^TA=begin{pmatrix}u_1 \ u_1+varepsilon u_2end{pmatrix}begin{pmatrix}u_1 & u_1+varepsilon u_2end{pmatrix}=begin{pmatrix}u_1^2 & u_1(u_1+varepsilon u_2)\u_1(u_1+varepsilon u_2) & (u_1 + varepsilon u_2)^2end{pmatrix}$



But when I try to compute $(A^TA)^{-1}$, determinant becomes zero, what means that matrix is not invertible. What am I doing wrong? Thanks in advance for any hints!










share|cite|improve this question







New contributor




Michael is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











I am trying to solve the following problem:




Let $u_1$ and $u_2$ be two orthogonal vectors in ${rm I!R}^n$ and
set $a_1 = u_1$, $a_2 = u_1 + varepsilon u_2$ for $varepsilon>0$.
Let also $A$ be the matrix with columns $a_1$ and $a_2$ and $b$ a
vector linearly independenet of $a_1$ and $a_2$. Least square solution
is discussed here to the system $Ax = b$ as $varepsilonto0$.



(a) Find the matrix $A^top A$, its inverse, and then $hat{x} =
> (A^top A)^{-1}A^top b$
explicitly. Show that $hat{x}$ explodes as
$varepsilonto0$



(b) Find the projection $Ahat{x}$ of $b$ onto $operatorname{col}(A)$
and check that it does not depend on $varepsilon>0$. Explain the
result.




I have assumed, that $A = begin{pmatrix}u_1 & u_1+varepsilon u_2end{pmatrix}$, therefore:



$A^TA=begin{pmatrix}u_1 \ u_1+varepsilon u_2end{pmatrix}begin{pmatrix}u_1 & u_1+varepsilon u_2end{pmatrix}=begin{pmatrix}u_1^2 & u_1(u_1+varepsilon u_2)\u_1(u_1+varepsilon u_2) & (u_1 + varepsilon u_2)^2end{pmatrix}$



But when I try to compute $(A^TA)^{-1}$, determinant becomes zero, what means that matrix is not invertible. What am I doing wrong? Thanks in advance for any hints!







least-squares






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New contributor




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New contributor





Michael is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.






Michael is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.












  • I guess that $A^T*A$ always has a zero determinant unless A is invertible.
    – NoChance
    yesterday


















  • I guess that $A^T*A$ always has a zero determinant unless A is invertible.
    – NoChance
    yesterday
















I guess that $A^T*A$ always has a zero determinant unless A is invertible.
– NoChance
yesterday




I guess that $A^T*A$ always has a zero determinant unless A is invertible.
– NoChance
yesterday










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Bear in mind what it means to multiply vectors in the first place. Your determinant is $$(u_1cdot u_1) (u_1cdot u_1 + 2varepsilon u_1cdot u_2+varepsilon^2 u_2cdot u_2)-(u_1cdot u_1 + varepsilon u_1cdot u_2)^2=varepsilon^2 (u_1cdot u_1 u_2cdot u_2-(u_1cdot u_2)^2).$$






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    Bear in mind what it means to multiply vectors in the first place. Your determinant is $$(u_1cdot u_1) (u_1cdot u_1 + 2varepsilon u_1cdot u_2+varepsilon^2 u_2cdot u_2)-(u_1cdot u_1 + varepsilon u_1cdot u_2)^2=varepsilon^2 (u_1cdot u_1 u_2cdot u_2-(u_1cdot u_2)^2).$$






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      Bear in mind what it means to multiply vectors in the first place. Your determinant is $$(u_1cdot u_1) (u_1cdot u_1 + 2varepsilon u_1cdot u_2+varepsilon^2 u_2cdot u_2)-(u_1cdot u_1 + varepsilon u_1cdot u_2)^2=varepsilon^2 (u_1cdot u_1 u_2cdot u_2-(u_1cdot u_2)^2).$$






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        Bear in mind what it means to multiply vectors in the first place. Your determinant is $$(u_1cdot u_1) (u_1cdot u_1 + 2varepsilon u_1cdot u_2+varepsilon^2 u_2cdot u_2)-(u_1cdot u_1 + varepsilon u_1cdot u_2)^2=varepsilon^2 (u_1cdot u_1 u_2cdot u_2-(u_1cdot u_2)^2).$$






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        Bear in mind what it means to multiply vectors in the first place. Your determinant is $$(u_1cdot u_1) (u_1cdot u_1 + 2varepsilon u_1cdot u_2+varepsilon^2 u_2cdot u_2)-(u_1cdot u_1 + varepsilon u_1cdot u_2)^2=varepsilon^2 (u_1cdot u_1 u_2cdot u_2-(u_1cdot u_2)^2).$$







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        answered yesterday









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