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    Source Separation and Machine Learning

    Source Separation and Machine Learning

    Af
    Bog E-bog
    • Format
    • Bog, paperback
    • Engelsk

    Beskrivelse

    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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    Detaljer
    • SprogEngelsk
    • Sidetal384
    • Udgivelsesdato23-10-2018
    • ISBN139780128177969
    • Forlag Academic Press Inc
    • FormatPaperback
    Størrelse og vægt
  • Vægt720 g
    • coffee cup img
    10 cm
    book img
    19,1 cm
    23,5 cm

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