Timeline for projection of a vector onto a vector space
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| May 30, 2020 at 21:32 | comment | added | amd | You could’ve saved yourself a lot of work by projecting orthogonally onto $A^\perp$ instead, which is only one-dimensional, and then subtracting that from $x$. You can read a vector that spans $A^\perp$ directly from the equation that defines $A$. | |
| May 30, 2020 at 21:18 | history | edited | José Carlos Santos | edited tags | |
| May 30, 2020 at 21:06 | comment | added | lambdaepsilon | working the real space would the minimization occur when the interior portion is equal to zero. Also its squared because you are projecting the distance between x and an arbitrary point on itself right? | |
| May 30, 2020 at 20:48 | answer | added | José Carlos Santos | timeline score: 2 | |
| May 30, 2020 at 20:48 | comment | added | Alexey Burdin | Once you have an orthonormal basis of $A$, say $e_1,e_2,e_3$ you can express an arbitrary point of $A$ as $te_1+ue_2+ve_3$ and compute $(x-(te_1+ue_2+ve_3))^2$, then take it to the minimum. | |
| May 30, 2020 at 20:42 | history | asked | lambdaepsilon | CC BY-SA 4.0 |