Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Non-negative matrix factorization with α-divergence
Pattern Recognition Letters
Blind Image Separation Using Nonnegative Matrix Factorization with Gibbs Smoothing
Neural Information Processing
Data Clustering with Semi-binary Nonnegative Matrix Factorization
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Robust Speaker Modeling Based on Constrained Nonnegative Tensor Factorization
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Continuous speech recognition with sparse coding
Computer Speech and Language
Computational Intelligence and Neuroscience - Advances in Nonnegative Matrix and Tensor Factorization
Non-negative matrix factorization Vs. FastICA on mismatch negativity of children
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Journal of Computer Science and Technology
A hierarchical framework for spectro-temporal feature extraction
Speech Communication
A new feature extraction and selection scheme for hybrid fault diagnosis of gearbox
Expert Systems with Applications: An International Journal
On spectral basis selection for single channel polyphonic music separation
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Csiszár’s divergences for non-negative matrix factorization: family of new algorithms
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Monaural music source separation: nonnegativity, sparseness, and shift-invariance
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Extended SMART algorithms for non-negative matrix factorization
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Non-monotone projection gradient method for non-negative matrix factorization
Computational Optimization and Applications
Multistability of α-divergence based NMF algorithms
Computers & Mathematics with Applications
Effects of architecture choices on sparse coding in speech recognition
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Solving non-negative matrix factorization by alternating least squares with a modified strategy
Data Mining and Knowledge Discovery
Modified subspace Barzilai-Borwein gradient method for non-negative matrix factorization
Computational Optimization and Applications
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A parts-based representation is a way of understanding object recognition in the brain. The nonnegative matrix factorization (NMF) is an algorithm which is able to learn a parts-based representation by allowing only non-subtractive combinations [Lee, D.D., Seung, H.S., 1999. Learning the parts of objects by non-negative matrix factorization. Nature 401, 788-791]. In this paper we incorporate a parts-based representation of spectro-temporal sounds into the acoustic feature extraction, which leads to nonnegative features. We present a method of inferring encoding variables in the framework of NMF and show that the method produces robust acoustic features in the presence of noise in the task of general sound classification. Experimental results confirm that the proposed feature extraction method improves the classification performance, especially in the presence of noise, compared to independent component analysis (ICA) which produces holistic features.