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Dear developer team
First of all, many thanks for the Py Sensors packages and the detailed and very clear examples! I am using SSPOR to optimize a hydrographs observation network. My data set consists of 480 sensors with 1304 features each. Now I would like to make reconstruction with more than 480 SVD basis modes (p>r). In the paper of Manohar e al (2018) I have found out that the oversampled case can be handled with ψrψrT. This should allow a maximum of 1304 basis modes?! Is there a possibility to integrate this into the SSPOR functionality?
Thanks for your help!
Marc
The text was updated successfully, but these errors were encountered:
Dear developer team
First of all, many thanks for the Py Sensors packages and the detailed and very clear examples! I am using SSPOR to optimize a hydrographs observation network. My data set consists of 480 sensors with 1304 features each. Now I would like to make reconstruction with more than 480 SVD basis modes (p>r). In the paper of Manohar e al (2018) I have found out that the oversampled case can be handled with ψrψrT. This should allow a maximum of 1304 basis modes?! Is there a possibility to integrate this into the SSPOR functionality?
Thanks for your help!
Marc
The text was updated successfully, but these errors were encountered: