Hi everyone,

I am currently doing research which applies RQA to EEG data. This toolbox is amazing and I really appreciate the genius sharing of Dr. Marwan for this software.

The problem I am dealing with involves multi-channel EEG, which means they have N*m matrix as an input, where N is number of channels and m is number of time points. Up to now, I compute RQA measures channel by channel - but it is really slow. I wonder how it works when I directly input the N*m matrix to the crqa function, because I found this in the file:

% The input vectors can be multi-column vectors, where

% each column will be used as a component of the

% phase-space vector. However, if the first column is

% monotonically increasing, it will be used as an

% time scale for plotting.

I am wondering about how this works in terms of computation. As I understand, this means we are going to use the entire column as a vector to represents the coordinates in the re-constructed space - however, how the embedded dimension works in this case? Or does it means all embedded dimensions are set to 1 (no embedded dimension)? Any ideas will be helpful. Thanks a lot!