Denoising 1000000 samples from TDS7104

[bowlingpin]

I would like to know how to denoise 1,000,000 samples of data acquired from TDS7104.

I acquire them in array .txt format. 

I using labview8.5.

I tried by looping the array comparing with the threshold but it took very long time.

Is there faster way.

Also, acquiring the 1,000,000 samples data from the equipment took quite some time.

I used the normal acquiring icons seen on the Tektronix 7000 examples.

Is there a faster way? 

[Dennis_Knutson]

First, there is no such thing as a .txt array. There are string and numeric arrays and there are .txt files. What do you mean?

Second, exactly what is the nature of the noise? What is the point of the loop and the comparison?

How long is 'quite some time'? Seconds, minutes, hours, days? How have you configured the scope to acquire that many samples? Are you acquiring all at once or repeatedly triggering and accumulating?

'Normal' icons is not a very good desciption. Provide the actual names of the functions and the parameters you are passing. The best way to provide this information is to attach your code.

[xdaf]

Dennis is right, you should provide further details about the signal you're trying to acquire: in case 100k samples are enough for your application, post-acquisition processing will be by far less time-consuming.

Anyway, when using a scope, noise filtering is commonly done in three ways:

- by limiting bandwidth with the integrated low-pass filters (should be 250MHz and 20MHz on TDS7104). I'm sure you already tried that.

- doing a mobile average on a certain number of sweeps (Under the Horizontal menu, activate "averaging" instead of "sample", and set the number of averaged WFMs according to your needs).

- Some modern scopes provide built-in digital filters for noise rejection: although my TDS7104 doesn't have'em, maybe it's only a software option, and can be installed by firmware upgrade...

This operation can be, of course, done on your PC after acquisition. But it can be really time-consuming, depending on the number of samples you're computing the mobile average on.

Hope this helps

Regards

Message Edited by xdaf on 01-08-2010 09:08 AM