Jerry wrote:
>Jessica wrote:
>> 1. Average sample rate is in the ms range, but can vary to seconds /
>> minutes when there is no activity to be measured.
>> 2. Most of the sample intervals are in the ms range, but accuracy down
>> to the microsecond is possible. However, at that level, mostly noise
>> is recorded. I want to downsample to one measurement per second or
>> even minute.
>> 3. I am not sure how to quantify this, the signal measured does
>> contain a lot of noise, but ideally, I would like to use a Hull Moving
>> Average to smooth the data.
>>
>> I appreciate your help.
>>
>> On Feb 1, 5:29 pm, Richard Owlett <rowl...@pcnetinc.com> wrote:
>>> Jessica wrote:
>>>> I am looking for an open-source smoother to down-sample data. I know
>>>> there are many such as Hull Moving average, but I have data logge
at
>>>> the ms scale at non-fixed time intervals and I want to sample it on
>>>> the second range at fixed time intervals. Does anyone know of a good
>>>> smoother to do this? The key is that the input data is not logged a
a
>>>> constant frequency.
>>> Can't answer your specific question. *BUT* I can suggest
>>> information to give so you can get a meaningful answer:
>>>
>>> 1. What is the average sample rate?
>>> 2. What is the minimum and maximum time between samples?
>>> 2a. Possibly, what is the distribution of sample intervals?
>>> 3. What is your desired fixed "sample rate"?
>>> 4. What accuracy constraints of fit of reconstructed signal to
>>> the actual? [Would linear interpolation between points be
>>> adequate or would a 310947 degree polynomial be needed?
>>> [Alright already, the degree was tongue in cheek, but intent
>>> was serious.]
>>>
>>> The art of getting "right answer" is asking "right question" ;>
>>> [I *KNOW* from personal embarrassing experience.]
>
>Another question: How does the sampling rate compare to the bandwidth o

>your data?

If this is the same application, and if I'm understanding correctly, ther
is no continuous form of the data:

http://groups.google.com/group/comp....25715e0becd9c/

Knowing the bandwidth would probably boil down to deciding whic
frequencies are "noise", but that doesn't necessarily mean a low-pas
filter is a good idea.

Jessica: what is stopping you from using the HMA that you want to use?
Is it a question of whether it's the right tool? I'm not familiar wit
this estimator (other than reading an article on it just now that gives
formula, but not much insight), but I would think it'd be important to com
up with a model (this is an art, and if you get it wrong, the results wil
probably not tell you; Rune has a lot of good stuff to say about this
of both the trends you want to track, as well as the "noise" you don't.
You might look for: random walks, periodic components (once a day, once a
hour, etc), random ramps, etc..