Nonnegative Matrix Factorization with Minimum Correlation and Volume Constrains
Nonnegative Matrix Factorization with Minimum Correlation and Volume Constrains is a scholarly work, published in 2022 in ''IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences''. The main subjects of the publication include Speech enhancement, matrix, matrix decomposition, pattern recognition, non-negative matrix factorization, indoor positioning system, volume (thermodynamics), Source separation, signal separation, computer science, artificial intelligence, independent component analysis, factorization, underdetermined system, and algorithm. As a motivation, this paper proposes to add the minimum volume and minimum correlation constrains (MCV) to the NMF algorithm, which makes the new algorithm named MCV-NMF algorithm suitable for underdetermined scenarios where the source signals satisfy mutual independent assumption.