رکورد قبلیرکورد بعدی

" Source separation and machine learning / "


Document Type : BL
Record Number : 872353
Main Entry : Chien, Jen-Tzung
Title & Author : Source separation and machine learning /\ Jen-Tzung Chien.
Publication Statement : London :: Academic Press, an imprint of Elsevier,, [2019]
: , ©2019
Page. NO : 1 online resource.
ISBN : 0128045779
: : 0128177969
: : 9780128045770
: : 9780128177969
: 9780128045664
Bibliographies/Indexes : Includes bibliographical references and index.
Abstract : 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.
Subject : Blind source separation.
Subject : Machine learning.
Subject : Blind source separation.
Subject : Machine learning.
Subject : TECHNOLOGY ENGINEERING / Mechanical.
Dewey Classification : ‭621.3822‬
LC Classification : ‭TK5102.9‬‭.C45 2019‬
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