bookOct 12, 2009Closed access

Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation

Abstract

This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF's various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD). NMF/NTF and their extensions are increasingly used as tools in signal and image processing, and data analysis, having garnered interest due to their capability to provide new insights and relevant information about the complex latent relationships in experimental data sets. It is suggested that NMF can provide meaningful components with physical interpretations; for example, in bioinformatics, NMF and its extensions have been successfully applied…

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1,595
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1.69
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100%
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Authors

4

Topics & keywords

Keywords
  • Non-negative matrix factorization
  • Cluster analysis
  • Computer science
  • Tensor (intrinsic definition)
  • Matrix decomposition
  • Algorithm
  • Theoretical computer science
  • Data mining
UN Sustainable Development Goals
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