Question

For reasons I’d rather not go into, I need to filter a set of values to reduce jitter. To that end, I need to be able to average a list of numbers, with the most recent having the greatest effect, and the least recent having the smallest effect. I’m using a sample size of 10, but that could easily change at some point.

Are there any reasonably simple aging algorithms that I can apply here?

Answer 1

• Have a look at the exponential smoothing. Fairly simple, and might be sufficient for your needs. Basically recent observations are given relatively more weight than the older ones.
• Also (depending on the application) you may want to look at various reinforcement learning techniques, for example Q-Learning or TD-Learning or generally speaking any method involving the discount.