کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4603364 1336958 2008 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Structured nonnegative matrix factorization with applications to hidden Markov realization and clustering
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات اعداد جبر و تئوری
پیش نمایش صفحه اول مقاله
Structured nonnegative matrix factorization with applications to hidden Markov realization and clustering
چکیده انگلیسی

In this paper, we study the structured nonnegative matrix factorization problem: given a square, nonnegative matrix P, decompose it as P=VAV⊤ with V and A nonnegative matrices and with the dimension of A as small as possible. We propose an iterative approach that minimizes the Kullback–Leibler divergence between P and VAV⊤ subject to the nonnegativity constraints on A and V with the dimension of A given. The approximate structured decomposition P≃VAV⊤ is closely related to the approximate symmetric decomposition P≃VV⊤. It is shown that the approach for finding an approximate structured decomposition can be adapted to solve the symmetric decomposition problem approximately. Finally, we apply the nonnegative decomposition VAV⊤ to the hidden Markov realization problem and to the clustering of data vectors based on their distance matrix.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Linear Algebra and its Applications - Volume 429, Issue 7, 1 October 2008, Pages 1409-1424