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Latent Variable Analysis and Signal Separation

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Cover of 'Latent Variable Analysis and Signal Separation'

Table of Contents

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    Book Overview
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    Chapter 1 Robust Multilinear Decomposition of Low Rank Tensors
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    Chapter 2 Multichannel Audio Modeling with Elliptically Stable Tensor Decomposition
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    Chapter 3 Sum Conditioned Poisson Factorization
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    Chapter 4 Curve Registered Coupled Low Rank Factorization
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    Chapter 5 Source Analysis and Selection Using Block Term Decomposition in Atrial Fibrillation
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    Chapter 6 Some Issues in Computing the CP Decomposition of NonNegative Tensors
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    Chapter 7 A Grassmannian Minimum Enclosing Ball Approach for Common Subspace Extraction
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    Chapter 8 Decoupling Multivariate Functions Using Second-Order Information and Tensors
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    Chapter 9 Nonnegative PARAFAC2: A Flexible Coupling Approach
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    Chapter 10 Applications of Polynomial Common Factor Computation in Signal Processing
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    Chapter 11 Joint Nonnegative Matrix Factorization for Underdetermined Blind Source Separation in Nonlinear Mixtures
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    Chapter 12 Image Completion with Nonnegative Matrix Factorization Under Separability Assumption
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    Chapter 13 Feature Selection in Weakly Coherent Matrices
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    Chapter 14 Variable Projection Applied to Block Term Decomposition of Higher-Order Tensors
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    Chapter 15 Accelerating Likelihood Optimization for ICA on Real Signals
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    Chapter 16 Orthogonally-Constrained Extraction of Independent Non-Gaussian Component from Non-Gaussian Background Without ICA
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    Chapter 17 A New Link Between Joint Blind Source Separation Using Second Order Statistics and the Canonical Polyadic Decomposition
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    Chapter 18 A Blind Source Separation Method Based on Output Nonlinear Correlation for Bilinear Mixtures
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    Chapter 19 Using Taylor Series Expansions and Second-Order Statistics for Blind Source Separation in Post-Nonlinear Mixtures
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    Chapter 20 New Classes of Blind Quantum Source Separation and Process Tomography Methods Based on Spin Component Measurements Along Two Directions
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    Chapter 21 Blind Signal Separation by Synchronized Joint Diagonalization
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    Chapter 22 Exploiting Structures of Temporal Causality for Robust Speaker Localization in Reverberant Environments
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    Chapter 23 Relative Transfer Function Estimation from Speech Keywords
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    Chapter 24 On the Number of Signals in Multivariate Time Series
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    Chapter 25 A Generative Model for Natural Sounds Based on Latent Force Modelling
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    Chapter 26 Independent Vector Analysis Exploiting Pre-learned Banks of Relative Transfer Functions for Assumed Target’s Positions
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    Chapter 27 Does k Matter? k-NN Hubness Analysis for Kernel Additive Modelling Vocal Separation
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    Chapter 28 The 2018 Signal Separation Evaluation Campaign
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    Chapter 29 Improving Single-Network Single-Channel Separation of Musical Audio with Convolutional Layers
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    Chapter 30 Training Strategies for Deep Latent Models and Applications to Speech Presence Probability Estimation
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    Chapter 31 Jointly Detecting and Separating Singing Voice: A Multi-Task Approach
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    Chapter 32 Multi-Resolution Fully Convolutional Neural Networks for Monaural Audio Source Separation
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    Chapter 33 Long-Term SNR Estimation Using Noise Residuals and a Two-Stage Deep-Learning Framework
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    Chapter 34 Improving Reverberant Speech Separation with Binaural Cues Using Temporal Context and Convolutional Neural Networks
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    Chapter 35 Generating Talking Face Landmarks from Speech
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    Chapter 36 An Approximate Message Passing Approach for DOA Estimation in Phase Noisy Environments
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    Chapter 37 An Expectation-Maximization Approach to Tuning Generalized Vector Approximate Message Passing
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    Chapter 38 A Study on the Benefits of Phase-Aware Speech Enhancement in Challenging Noise Scenarios
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    Chapter 39 Phase Reconstruction for Time-Frequency Inpainting
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    Chapter 40 Revisiting Synthesis Model in Sparse Audio Declipper
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    Chapter 41 Consistent Dictionary Learning for Signal Declipping
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    Chapter 42 Learning Fast Dictionaries for Sparse Representations Using Low-Rank Tensor Decompositions
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    Chapter 43 Truncated Variational Sampling for ‘Black Box’ Optimization of Generative Models
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    Chapter 44 Using Hankel Structured Low-Rank Approximation for Sparse Signal Recovery
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    Chapter 45 Probabilistic Sparse Non-negative Matrix Factorization
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    Chapter 46 Application of Independent Component Analysis to Tumor Transcriptomes Reveals Specific and Reproducible Immune-Related Signals
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    Chapter 47 Probit Latent Variables Estimation for a Gaussian Process Classifier: Application to the Detection of High-Voltage Spindles
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    Chapter 48 Spatial Filtering of EEG Signals to Identify Periodic Brain Activity Patterns
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    Chapter 49 Static and Dynamic Modeling of Absence Epileptic Seizures Using Depth Recordings
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    Chapter 50 Multichannel Audio Source Separation Exploiting NMF-Based Generic Source Spectral Model in Gaussian Modeling Framework
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    Chapter 51 Perceptual Evaluation of Blind Source Separation in Object-Based Audio Production
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    Chapter 52 Muticriteria Decision Making Based on Independent Component Analysis: A Preliminary Investigation Considering the TOPSIS Approach
Attention for Chapter 39: Phase Reconstruction for Time-Frequency Inpainting
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Chapter title
Phase Reconstruction for Time-Frequency Inpainting
Chapter number 39
Book title
Latent Variable Analysis and Signal Separation
Published by
Springer, Cham, July 2018
DOI 10.1007/978-3-319-93764-9_39
Book ISBNs
978-3-31-993763-2, 978-3-31-993764-9

A. Marina Krémé, Valentin Emiya, Caroline Chaux

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 2 100%
Readers by discipline Count As %
Computer Science 2 100%