Finding an Upper bound of a matrix
$begingroup$
How do I find the upper bound of $left( v^{T}U_{n}D_{nn}U_{n}vright)$ where $v$ is the covariance between each point $x_i$ in a domain $D$ and a new location $x*$. $U_{n};text{and}; D_{nn}$ are the eigenvectors and eigenvalues of a matrix $A$. So I know I can write $v = sigma^{2}rho^{2}(x_i,x*)$ but bounding $left( v^{T}U_{n}D_{nn}U_{n}vright)$ has been a challenge to me. I was reading a paper on uniform error bound but I think,Its way different from what I seek to achieve. Any help or hint on how to proceed will be much appreciated.
matrices upper-lower-bounds
asked Dec 6 '18 at 9:39
KsmithKsmith
213
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add a comment |
$begingroup$
How do I find the upper bound of $left( v^{T}U_{n}D_{nn}U_{n}vright)$ where $v$ is the covariance between each point $x_i$ in a domain $D$ and a new location $x*$. $U_{n};text{and}; D_{nn}$ are the eigenvectors and eigenvalues of a matrix $A$. So I know I can write $v = sigma^{2}rho^{2}(x_i,x*)$ but bounding $left( v^{T}U_{n}D_{nn}U_{n}vright)$ has been a challenge to me. I was reading a paper on uniform error bound but I think,Its way different from what I seek to achieve. Any help or hint on how to proceed will be much appreciated.
matrices upper-lower-bounds
asked Dec 6 '18 at 9:39
KsmithKsmith
213
$endgroup$
add a comment |
$begingroup$
How do I find the upper bound of $left( v^{T}U_{n}D_{nn}U_{n}vright)$ where $v$ is the covariance between each point $x_i$ in a domain $D$ and a new location $x*$. $U_{n};text{and}; D_{nn}$ are the eigenvectors and eigenvalues of a matrix $A$. So I know I can write $v = sigma^{2}rho^{2}(x_i,x*)$ but bounding $left( v^{T}U_{n}D_{nn}U_{n}vright)$ has been a challenge to me. I was reading a paper on uniform error bound but I think,Its way different from what I seek to achieve. Any help or hint on how to proceed will be much appreciated.
matrices upper-lower-bounds
asked Dec 6 '18 at 9:39
KsmithKsmith
213
$endgroup$
How do I find the upper bound of $left( v^{T}U_{n}D_{nn}U_{n}vright)$ where $v$ is the covariance between each point $x_i$ in a domain $D$ and a new location $x*$. $U_{n};text{and}; D_{nn}$ are the eigenvectors and eigenvalues of a matrix $A$. So I know I can write $v = sigma^{2}rho^{2}(x_i,x*)$ but bounding $left( v^{T}U_{n}D_{nn}U_{n}vright)$ has been a challenge to me. I was reading a paper on uniform error bound but I think,Its way different from what I seek to achieve. Any help or hint on how to proceed will be much appreciated.
matrices upper-lower-bounds
matrices upper-lower-bounds
asked Dec 6 '18 at 9:39
KsmithKsmith
213
asked Dec 6 '18 at 9:39
KsmithKsmith
213
asked Dec 6 '18 at 9:39
KsmithKsmith
213
asked Dec 6 '18 at 9:39
KsmithKsmith
213
asked Dec 6 '18 at 9:39
KsmithKsmith
213
213
add a comment |
add a comment |
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