in multilinear algebra, the tensor rank decomposition or canonical polyadic decomposition (cpd) may be regarded as a generalization of the matrix singular value decomposition (svd) to tensors, which has found application in statistics, signal processing, psychometrics, linguistics and chemometrics. it was introduced by hitchcock in 1927 and later rediscovered several times, notably in psychometrics.