Timeline for Black box signal prediction
Current License: CC BY-SA 3.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jan 30, 2012 at 16:38 | comment | added | Phonon | @AdamCrume Indeed. These problems are very computationally demanding and many papers published on this stuff actually deal with algorithm optimization rather that with new ways to approach the problems. | |
| Jan 30, 2012 at 16:29 | comment | added | Adam Crume | After looking at it for a while, I think I did something similar. I built a polynomial from x1(t), x2(t), ..., x1(t-1), x2(t-1), ... and tried to learn the coefficients using gradient descent. The problem is, just an order four polynomial looking back two time steps requires something like a thousand parameters. | |
| Jan 27, 2012 at 18:47 | comment | added | Phonon | I'm sure you can find a state-space representation of the above equation. That will deal with multiple inputs quite easily. | |
| Jan 27, 2012 at 18:35 | comment | added | Adam Crume | That's certainly interesting, but I have an input vector at each time step, and this seems to only work with scalars. | |
| Jan 27, 2012 at 15:05 | history | answered | Phonon | CC BY-SA 3.0 |