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Non-negative 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 non-negative constraints. This problem attracts 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 Lee and Seung. In this paper, we propose an additive update algorithm that has a faster computational speed than Lee and Seung's multiplicative update algorithm.

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