Source separation and machine learning 1st edition

Source separation and machine learning 1st edition- Ebook Instant Download/Delivery ISBN(s): 9780128045770,9780128177969,0128045779,0128177969

Product details:

ISBN 10: 0128045779

ISBN 13: 9780128045770

Author: Jen-Tzung Chien

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.

Table contents:

Chapter 1: Introduction

Chapter 2: Model-Based Source Separation

Chapter 3: Adaptive Learning Machine

Chapter 4: Independent Component Analysis

Chapter 5: Nonnegative Matrix Factorization

Chapter 6: Nonnegative Tensor Factorization

Chapter 7: Deep Neural Network

Chapter 8: Summary and Future Trends

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