Jen-Tzung Chien,
Jen-Tzung (Chair Professor, Department of Electrical and Computer Engineering, National Chiao Tung University, Taiwan) Chien
Source Separation and Machine Learning
Paperback Engels 2018 9780128177969Levertijd ongeveer 9 werkdagen
Gratis verzonden
Samenvatting
Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the importance of machine learning perspectives. It illustrates how BSS problems are tackled through adaptive learning algorithms and model-based approaches using the latest information on mixture signals to build a BSS model that is seen as a statistical model for a whole system. Looking at different models, including independent component analysis (ICA), nonnegative matrix factorization (NMF), nonnegative tensor factorization (NTF), and deep neural network (DNN), the book addresses how they have evolved to deal with multichannel and single-channel source separation.
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Inhoudsopgave
<p>Part I Fundamental Theories1. Introduction2. Model-based blind source separation3. Adaptive learning machine</p> <p>Part II Advanced Studies4. Independent component analysis5. Nonnegative matrix factorization6. Nonnegative tensor factorization7. Deep neural network8. Summary and Future Trends</p>
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