Timeline for Algorithm for finding eigenfunctions
Current License: CC BY-SA 3.0
11 events
| when toggle format | what | by | license | comment | |
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| Oct 14, 2015 at 0:34 | review | Close votes | |||
| Oct 15, 2015 at 17:14 | |||||
| Oct 14, 2015 at 0:05 | comment | added | user66731 | The $ \partial \phi(a, b) $ is my a, b space measure. | |
| Oct 14, 2015 at 0:03 | comment | added | user66731 | I edited it thinking of a different problem I am working on. If you saw the change ignore it. I changed it back. My general goal is to take a family of functions $ \{ f_a \} $, and take all translations (could be discrete if this is easier) of these functions and extract a "covariance" matrix of these functions localized in a gaussian window as vectors in a Hilbert space. I am doing Principle Component Analysis on these vectors, but first localizing them in space. Thus I can ask what the principle localized components are and use this to decompose other functions into orthogonal components. | |
| Oct 13, 2015 at 23:55 | history | edited | user66731 | CC BY-SA 3.0 |
[Edit removed during grace period]
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| Oct 13, 2015 at 23:44 | comment | added | Francois Ziegler | What is $\partial$? (Some sort of $d$?) What is $\int\partial\phi(a,b)\dots$? (Some sort of Stieltjes integral?) What is $a$? (Some sort of number?) How does $f_a$ depend on it? (Arbitrarily?) Etc. | |
| Oct 13, 2015 at 23:17 | comment | added | user66731 | I just did. Please let me know if you need more detail. | |
| Oct 13, 2015 at 23:16 | history | edited | user66731 | CC BY-SA 3.0 |
added 304 characters in body
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| Oct 12, 2015 at 21:58 | comment | added | Carlo Beenakker | somehow I have difficulty parsing your formula for $\Omega$; could you write down explictly how $\Omega$ acts on a function in $L^2(\mathbb{R})$ ? | |
| Oct 12, 2015 at 21:35 | history | edited | Stefan Kohl♦ | CC BY-SA 3.0 |
Added top-level tag.
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| Aug 20, 2015 at 17:57 | review | First posts | |||
| Aug 20, 2015 at 18:07 | |||||
| Aug 20, 2015 at 17:55 | history | asked | user66731 | CC BY-SA 3.0 |