 Tensor rank decomposition

Tensor rank decomposition is a mathematical concept used to express a tensor as a sum of simpler tensors, often referred to as "rank-one tensors." Tensors can be thought of as multi-dimensional arrays, and they generalize matrices (which are two-dimensional tensors) to higher dimensions.