Timeline for Combining different Likelihoods - Particle Filter
Current License: CC BY-SA 3.0
9 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Sep 28, 2017 at 9:00 | vote | accept | J. Doe | ||
| Sep 15, 2017 at 1:31 | history | tweeted | twitter.com/StackSignals/status/908503416795799558 | ||
| Sep 13, 2017 at 15:58 | answer | added | Atul Ingle | timeline score: 1 | |
| Sep 13, 2017 at 15:42 | comment | added | Atul Ingle | Thanks. You are right, the transition model is not relevant (for now). Now if the noise components are independent, the $\approx$ symbols in your equation can all be turned into $=$. So, correlations between state variable is probably not the issue here. You may need to elaborate more on the "this does not work very well" part of your question. | |
| Sep 13, 2017 at 14:52 | comment | added | J. Doe | $z$ is the observation and the obsv. model is given by $z=x$+noise. The transition function is given by a non-linear function $f(x)$ but I dont see how it would be important for the observation likelihood if we use a sequential approach? | |
| Sep 12, 2017 at 17:59 | comment | added | Atul Ingle | What is the observation model? Is $z$ the observation and $z = x+$noise? Also, what's the state transition model? | |
| Sep 12, 2017 at 15:40 | history | edited | J. Doe | CC BY-SA 3.0 |
additional information/better explanation due to the lack of answers
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| Sep 12, 2017 at 9:04 | review | First posts | |||
| Sep 12, 2017 at 11:15 | |||||
| Sep 12, 2017 at 9:02 | history | asked | J. Doe | CC BY-SA 3.0 |