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[R] Dimensionality reduction techniques for multivariate time series?
The title is quite a mouthful, but I'm trying to learn about how a multivariate (high dimensional) time series can be reduced to a lower amount of time series to be used in regression. In the same way that an image can be compressed into a smaller latent space using Autoencoders, I am trying to read up on how these N signals can be compressed into n<<N more salient signals. Say you had 100 EMG signals, what techniques are there …!-->