Written for students and researchers, Multilinear Subspace Learning gives a comprehensive introduction to both theoretical and practical aspects of MSL for the dimensionality reduction of multidimensional data based on tensors. It covers the fundamentals, algorithms, and applications of MSL. Topics include tensor representation of multidimensional data, principal component analysis, and multilinear algebra preliminaries.
In addition, a supplemental set of MATLAB code files is available for download.
Teaching materials based on MATLAB and Simulink