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Using A Kalman Filter To Make Sense Of Noisy Data

89 points| jack7890 | 14 years ago |seatgeek.com | reply

18 comments

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[+] dredmorbius|14 years ago|reply
Yet another blog which, if visited without JS enabled, displays a rather disconcertingly unrelated page (ticket search).

Noscript -> seatgeek.com -> Temp

(For anyone else confused by the apparent topic/content discrepancy).

And for those interested in a more readable technical explanation, there's the Wikipedia article (linked from the seatgeek blog): https://duckduckgo.com/lite

[+] jack7890|14 years ago|reply
Good point, we will absolutely fix this.

If you don't mind me asking, why are you visiting websites without JS?

[+] jack7890|14 years ago|reply
If there are other folks interested in using this approach, drop us a line. We're happy to try to help other startups make sense of their data.
[+] jianshen|14 years ago|reply
I was working with Kalman filters for a hardware project and had serious trouble wrapping my head around the topic.

I ended up confusing a Kalman Filter with a plain old Low Pass Filter at first (and you can reduce a Kalman filter to that if you don't have enough inputs) but it really is quite a powerful tool.

It's neat to see it applied to a different problem that might make it easier for novices (like myself) to understand. Thanks for posting!

[+] pork|14 years ago|reply
Any thoughts on writing up similar articles about more advanced nonlinear filters, like particle filters?
[+] essayist|14 years ago|reply
Useful.

I'd love to find FAAS - Kalman (and other) filtering as a service.

For instance: I run daily backups on various databases. I expect the backup size to increase roughly linearly, but I'm just going to look in on the backups at random, likely ignoring them for months at a time.

It'd be great to be able to run the backup size series through a filter that would alert me when something unexpected happened, e.g. slope changes significantly or some unusual step change.

[+] jnazario|14 years ago|reply
great post, and thanks for sharing it. i came across the kalman filter after developing an algorithm to detect worm propagation. it applies equally well in that scenario, basically predictions.
[+] derekja|14 years ago|reply
Very nice post, thanks!