For sparse data, sparse formats can significantly increase speed and reduce memory requirements. However, MATLAB’s built-in sparse format represents only vectors and matrices, not N-dimensional arrays (tensors). This toolbox contains a new "sparse array structure" and associated operations – outer, entrywise, and inner products, addition, summation, convolution, distance measures, permutation, (circular) shifts, and other manipulations – that can be applied to N-dimensional full arrays or to sparse array structures. All functions have been carefully designed to optimize speed.
For more information, see SparseArrayToolbox.pdf.
This work forms part of an Australian Research Council Discovery Early Career Researcher Award (project number DE170100353) funded by the Australian Government.