Demos

This collection of demos has as goal to introduce Tensorlab to users as a tool to solve tensor problems. We begin with a demo about the basic use of Tensorlab followed by a demo about the multilinear singular value decomposition and the low multilinear rank approximation. In the other demos, the usage of Tensorlab is illustrated for several applications. The list is far from complete, but should give readers from various domains examples of how the software can be used. The second demo discusses the multidimensional harmonic retrieval problem. The demo Using basic Tensorlab features for ICA uses basic tensor tools to solve the independent component analysis (ICA) problem. ICA is also discussed in the Using advanced Tensorlab features for ICA demo, which applies the structured data fusion (SDF) framework from Tensorlab to implement constrained decompositions. Furthermore, SDF is also illustrated for independent vector analysis (IVA), and for user involvement prediction based on a GPS dataset.

Matlab-scripts for the demos can be downloaded here, or from their respective pages. A PDF version of the demos can be found here.

• Basic use of Tensorlab
• Multilinear singular value decomposition and low multilinear rank approximation
• Multidimensional harmonic retrieval
• Using basic Tensorlab features for ICA
• Using advanced Tensorlab features for ICA
• Independent vector analysis
• GPS Demo: predicting user involvement
• References