Low-M-Rank Tensor Completion and Robust Tensor PCA
Low-M-Rank Tensor Completion and Robust Tensor PCA is a scholarly work, published in 2018 in ''IEEE Journal on Selected Topics in Signal Processing''. The main subjects of the publication include tensor decomposition, tensor field, super-resolution imaging, robust principal component analysis, tensor density, tensor completion, singular value decomposition, compressed sensing, rank, symmetric tensor, mathematics, tensor, Cartesian tensor, and combinatorics. The authors propose a new approach to solve low-rank tensor completion and robust tensor PCA.