Training Autoencoder on time series with repeating pattern

cross-posted from: https://sh.itjust.works/post/67956

Not OP. This question is being reposted to preserve technical content removed from elsewhere. Feel free to add your own answers/discussion.

Original question:

Im training an autoencoder on a time series that consists of repeating patterns (because the same process is repeated again and again). If I then use this autoencoder to reconstruct another one of these patterns, I expect the reconstruction to be worse if the pattern is different from the ones it has been trained on.

Is the fact that the sime series consists of repeating patterns something that needs to be considered in any way for training or data preprocessing? I am currently using this on raw channels.

Thank you.