Editing Rank (linear algebra) (section)

=== Tensor rank – minimum number of simple tensors ===
{{Main|Tensor rank decomposition|Tensor rank}}

The rank of {{mvar|A}} is the smallest number {{mvar|k}} such that {{mvar|A}} can be written as a sum of {{mvar|k}} rank 1 matrices, where a matrix is defined to have rank 1 if and only if it can be written as a nonzero product <math>c \cdot r</math> of a column vector {{mvar|c}} and a row vector {{mvar|r}}.  This notion of rank is called [[tensor rank]]; it can be generalized in the [[Singular value decomposition#Separable models|separable models]] interpretation of the [[singular value decomposition]].