  Nonnegative matrix factorization (NMF) is an emerging technique with a wide
spectrum of potential applications in data analysis. Mathematically, NMF can be
formulated as a minimization problem with nonnegative constraints. This problem
is currently attracting much attention from researchers for theoretical reasons
and for potential applications. Currently, the most popular approach to solve
NMF is the multiplicative update algorithm proposed by D.D. Lee and H.S. Seung.
In this paper, we propose an additive update algorithm, that has faster
computational speed than the algorithm of D.D. Lee and H.S. Seung.
