How do I prepare a MDF Datastore for training a neural Network? (Deep Network Designer)

Hi there,

I want to build a neural network that predicts certain quantities of a cars dynamics. To keep it simple, let's say I want to predict the cars acceleration depending on the throttle position. I have a lot of mf4 files of the car driving around, containing data of the throttle position and the acceleration. I import them using mdfRead

How do I prepare the data so that I can load it into the Deep Network Designer?

I basically have two problems: The files contain a lot of quantities (aka channels) that I don't need and the channels I need are in different channel groups.

What I tried so far is to follow this guide: https://de.mathworks.com/help/vnt/ug/write-channel-group-data-from-existing-mdf-file-to-new-mdf-file.html which basically copies all the needed channels into a new timetable and saves that as a new mdf file. The problem is that the channels use different sampling rates and therefore the timetables have different sizes and I get "Error using . To assign to or create a variable in a table, the number of rows must match the height of the table."

Whats the best way to fix that or is my approach complete nonsense?