Computational Intelligence and Neuroscience / 2008 / Article / Alg 1

Research Article

Pattern Expression Nonnegative Matrix Factorization: Algorithm and Applications to Blind Source Separation

Algorithm 1

Learning algorithm.
Algorithm parameters: ;
Input: an n by m nonnegative observation matrix V;
Output: an n by r nonnegative matrix W and an r by m
nonnegative matrix H.
Step 1: set , and generate nonnegative matrix and
at random;
Step 2: Update from to by
where I is an r by m matrix full of elements being 1s, and M
is an r by r matrix with all elements being 1s except diagonal
elements being zeros.
Step 3: Increment t by and go to step 2 until
and converge.

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