- #1
thegreenlaser
- 525
- 16
I don't have a ton of experience in numerical methods, so I'm hoping someone can help me out. Suppose I have a sequence of position data points for a car, but they've been truncated to integer values. I want to find the speed (derivative), but for speeds which are low relative to the time between measurements, I find that repeated measurements kill my evaluation of the derivative. For example, if the actual position sequence of the car was {0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9}, it would be measured as {0, 0, 0, 0, 1, 1, 1, 1, 1}. So if I apply a simple difference operator, instead of getting a constant speed like the actual position sequence implies, I would be getting mostly zero speed with a sudden spike at the point where the measured position changes from 0 to 1.
So my question is, how do I properly differentiate data that looks truncated or stepped like this? (noting that I need to be able to do it in real time, i.e. without using any future data points) I've tried a few different things, but have only had marginal success. Any suggestions would be greatly appreciated.
So my question is, how do I properly differentiate data that looks truncated or stepped like this? (noting that I need to be able to do it in real time, i.e. without using any future data points) I've tried a few different things, but have only had marginal success. Any suggestions would be greatly appreciated.