Latent Variable Analysis and Signal Separation [[electronic resource] ] : 13th International Conference, LVA/ICA 2017, Grenoble, France, February 21-23, 2017, Proceedings / / edited by Petr Tichavský, Massoud Babaie-Zadeh, Olivier J.J. Michel, Nadège Thirion-Moreau |
Edizione | [1st ed. 2017.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
Descrizione fisica | 1 online resource (XVI, 576 p. 174 illus.) |
Disciplina | 621.3822 |
Collana | Theoretical Computer Science and General Issues |
Soggetto topico |
Pattern recognition systems
Computer vision Artificial intelligence Computer simulation Numerical analysis Computer networks Automated Pattern Recognition Computer Vision Artificial Intelligence Computer Modelling Numerical Analysis Computer Communication Networks |
ISBN | 3-319-53547-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Tensor Approaches -- Higher-Order Block Term Decomposition for Spatially Folded fMRI Data -- 1 Introduction -- 1.1 Notation -- 2 Tensorial fMRI Analysis -- 2.1 Canonical Polyadic Decomposition (CPD) -- 2.2 Tensor Probabilistic Independent Component Analysis (TPICA) -- 3 Block Term Decomposition (BTD) for fMRI -- 3.1 Uniqueness -- 4 Simulation Results -- 4.1 Simulation of a Perception Study -- 4.2 Multi-slice Simulation -- 5 Conclusions -- References -- Modeling Parallel Wiener-Hammerstein Systems Using Tensor Decomposition of Volterra Kernels -- 1 Introduction -- 2 Volterra Kernels, Tensors and Tensor Decomposition -- 2.1 The Volterra Model for Nonlinear Systems -- 2.2 From Polynomials to Tensors -- 2.3 Canonical Polyadic Decomposition -- 3 Parallel Wiener-Hammerstein as Tensor Decomposition -- 3.1 Wiener-Hammerstein as Structured Tensor Decomposition -- 3.2 Parallel Wiener-Hammerstein Structure -- 3.3 Coupled Tensor and Matrix Decompositions -- 4 Numerical Results -- 5 Conclusions -- References -- Fast Nonnegative Matrix Factorization and Completion Using Nesterov Iterations -- 1 Introduction -- 2 Standard NeNMF -- 3 Extending NeNMF to Missing Entries -- 3.1 Weigthed Extension of NeNMF -- 3.2 EM Extension of NeNMF -- 4 Performance of the Weighted NeNMF Extensions -- 5 Conclusion -- A Proof of Lemmas 1 and 2 -- References -- Blind Source Separation of Single Channel Mixture Using Tensorization and Tensor Diagonalization -- 1 Introduction -- 2 General Framework for BSS of Single Channel Mixture -- 3 Tensorization of Sinusoid Signals -- 3.1 Two-Way and Three-Way Foldings -- 3.2 Toeplitzation -- 4 Simulations -- 5 Conclusions -- A Appendix: Low-Rank Representation of the Sequence x(t) = tn -- References -- High-Resolution Subspace-Based Methods: Eigenvalue- or Eigenvector-Based Estimation?.
1 Introduction -- 2 Multilevel Hankel Matrices and Their Subspaces -- 2.1 Definition and Factorization -- 2.2 Shift Properties of Subspaces -- 3 ESPRIT-Type Algorithms for MH Matrices -- 3.1 N-D ESPRIT Algorithm -- 3.2 IMDF Algorithm -- 3.3 IMDF Based on Least Squares (IMDF LS) -- 4 Perturbation Analysis -- 4.1 Basic Expressions -- 4.2 IMDF Perturbations -- 4.3 IMDF LS Perturbations -- 4.4 Computing the First-Order Perturbation and Its Moments -- 5 Simulations -- 6 Conclusions -- References -- From Source Positions to Room Properties: Learning Methods for Audio Scene Geometry Estimation -- Speaker Tracking on Multiple-Manifolds with Distributed Microphones -- 1 Introduction -- 2 Problem Formulation -- 3 Multiple-Manifold Gaussian Process -- 4 Multiple-Manifold Speaker Tracking -- 5 Experimental Study -- 6 Conclusions -- References -- VAST: The Virtual Acoustic Space Traveler Dataset -- 1 Introduction -- 2 Dataset Design -- 2.1 General Principles -- 2.2 Room Simulation and Data Generation -- 2.3 Room Properties: Size and Surfaces -- 2.4 Reverberation Time -- 2.5 Source and Receiver Positions -- 2.6 Test Sets -- 3 Virtually Supervised Sound Source Localization -- 4 Conclusion -- References -- Sketching for Nearfield Acoustic Imaging of Heavy-Tailed Sources -- 1 Introduction -- 2 Mixture Model and -Stable Theory -- 2.1 Notation and Convolutive Model -- 2.2 Independent Isotropic -Stable Model for the Sources -- 2.3 The Levy Exponent and the Spatial Measure -- 3 Parameter Estimation -- 3.1 Sketching for the Levy Exponent -- 3.2 A Proposed NMF Algorithm to Determine -- 4 Evaluation -- 5 Conclusion -- References -- Acoustic DoA Estimation by One Unsophisticated Sensor -- 1 Introduction -- 2 Localization of Noise Sources -- 2.1 Geometrical Structure -- 2.2 Structure Quality -- 2.3 Conditions for Localization -- 3 Algorithms -- 3.1 Subspace Model. 3.2 Dictionary Model -- 4 Numerical Results -- 4.1 White Sources -- 4.2 Speech Sources -- 5 Conclusion -- References -- Acoustic Source Localization by Combination of Supervised Direction-of-Arrival Estimation with Disjoint Component Analysis -- 1 Introduction -- 2 Methods -- 2.1 Probabilistic Source Localization -- 2.2 Disjoint Component Analysis -- 2.3 Decomposition of Source Probability Map -- 2.4 Multi-channel Signal Enhancement -- 3 Experiments and Results -- 4 Summary and Discussion -- References -- Tensors and Audio -- An Initialization Method for Nonlinear Model Reduction Using the CP Decomposition -- 1 Introduction -- 2 Notations and Problem Statement -- 3 Finding an Appropriate Initialization -- 4 Simulations and Results -- 5 Case Study -- 6 Conclusion -- References -- Audio Zoom for Smartphones Based on Multiple Adaptive Beamformers -- 1 Introduction -- 2 Proposed Audio Zoom System -- 2.1 Target Sound Source Enhancement -- 2.2 Proposed Audio Zoom Effect Creation -- 3 Experiments -- 3.1 Experiment Setup -- 3.2 Result with Subjective Test -- 4 Conclusion -- References -- Complex Valued Robust Multidimensional SOBI -- 1 Introduction -- 2 Preliminaries -- 3 Algorithms -- 3.1 SOBI -- 3.2 Affine Equivariant SAM-SOBI -- 3.3 Multidimensional SOBI -- 3.4 Robust Multidimensional SOBI -- 4 Simulation Study -- 5 Conclusions -- References -- Ego Noise Reduction for Hose-Shaped Rescue Robot Combining Independent Low-Rank Matrix Analysis and Multichannel Noise Cancellation -- 1 Introduction -- 2 Hose-Shaped Rescue Robot and Ego Noise -- 2.1 Hose-Shaped Rescue Robot -- 2.2 Problem in Recording Speech -- 3 Overview of Independent Low-Rank Matrix Analysis -- 3.1 Formulation -- 3.2 Independent Low-Rank Matrix Analysis -- 4 Multichannel Noise Canceller -- 4.1 Conventional Method -- 4.2 Proposed Method -- 4.3 Flow of the Proposed Method -- 5 Experiment. 5.1 Conditions -- 5.2 Results -- 6 Conclusion -- References -- Some Theory on Non-negative Tucker Decomposition -- 1 Tensor Decomposition Models -- 1.1 Tucker Decompositions -- 1.2 Canonical Polyadic Decomposition -- 2 Propagating Non-negativity and Non-negative Rank Through NTD -- 2.1 Elements of Cone Theory -- 2.2 Working Hypotheses -- 2.3 Propagating the Non-negative Rank to the Core -- 2.4 Propagating Non-negativity to the Core -- 3 Simulations -- 3.1 Some Algorithms for NTD and NMF -- 3.2 Some Tests on the Outputs of Algorithms -- 4 Conclusion -- References -- A New Algorithm for Multimodal Soft Coupling -- 1 Introduction -- 2 Soft Coupling for NMF -- 2.1 NMF Model -- 2.2 Coupled NMF -- 3 The Proposed Algorithm -- 3.1 Update Rule for Updating H1 -- 3.2 Update Rule for Updating -- 4 Experimental Results -- 5 Conclusion -- References -- Adaptive Blind Separation of Instantaneous Linear Mixtures of Independent Sources -- 1 Introduction -- 2 Signal Model and Separation Performance Limits -- 3 Adaptive BSS Algorithms -- 3.1 Scaled Stochastic Natural Gradient Algorithm -- 3.2 Adaptive BGSEP -- 3.3 Adaptive BARBI -- 4 Experiments -- 5 Conclusion -- References -- Source Separation, Dereverberation and Noise Reduction Using LCMV Beamformer and Postfilter -- 1 Introduction -- 2 Problem Formulation -- 3 Optimal Multichannel Speaker Separation, Dereverberation and Noise Reduction -- 4 Estimation of the Late Reverberation PSD Matrix -- 4.1 Estimator Based on a Temporal Model -- 4.2 Estimator Based on a Spatial Model -- 5 Performance Evaluation -- 5.1 Setup -- 5.2 Results -- 6 Conclusions -- References -- Toward Rank Disaggregation: An Approach Based on Linear Programming and Latent Variable Analysis -- 1 Introduction -- 2 Rank Aggregation -- 2.1 Rank-Aggregation as an Optimization Problem -- 2.2 Criteria for Rank Aggregation. 2.3 Numerical Example: CAC 40 Ranking of the Top 10 French Companies -- 3 Towards Rank Disaggregation -- 3.1 Rank Disaggregation via a Multivariate Decomposition Approach -- 3.2 Numerical Experiment -- 4 Conclusion -- References -- A Proximal Approach for Nonnegative Tensor Decomposition -- 1 Introduction -- 2 Canonical Polyadic Decomposition of N-th Order Tensors -- 2.1 Model -- 2.2 Objective -- 3 Optimization Problem and Proximal Algorithm -- 3.1 Criterion Formulation, Assumptions and Properties -- 3.2 Proposed Algorithm -- 3.3 Criterion Choice: Related Gradient and Proximity Operators -- 4 Numerical Simulations: Application to 4-th Order CPD -- 5 Conclusion -- References -- Psychophysical Evaluation of Audio Source Separation Methods -- Abstract -- 1 Introduction -- 2 Method -- 3 Results: Analysis I - Psychophysical Correlation -- 4 Results: Analysis II - Comparison of Separation Methods -- 5 Conclusion and Discussion -- Acknowledgment -- References -- Audio Signal Processing -- On the Use of Latent Mixing Filters in Audio Source Separation -- 1 Introduction -- 2 Latent Mixing Filters and Estimation of Source Image -- 2.1 Principle -- 2.2 General Expression of the Source Image MMSE Estimator -- 2.3 The Gaussian Case -- 2.4 Inference of Source Image Using Metropolis Algorithm -- 3 Experiments -- 4 Conclusion -- References -- Discriminative Enhancement for Single Channel Audio Source Separation Using Deep Neural Networks -- 1 Introduction -- 2 Problem Formulation of Audio SCSS -- 3 DNNs for source separation and enhancement -- 3.1 Training DNN-A for Source Separation -- 3.2 Training DNN-B for Discriminative Enhancement -- 3.3 Testing DNN-A and DNN-B -- 4 Experiments and Discussion -- 5 Conclusion -- References -- Audiovisual Speech Separation Based on Independent Vector Analysis Using a Visual Voice Activity Detector -- 1 Introduction. 2 Mathematical Preliminaries. |
Record Nr. | UNISA-996466077503316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Latent Variable Analysis and Signal Separation [[electronic resource] ] : 13th International Conference, LVA/ICA 2017, Grenoble, France, February 21-23, 2017, Proceedings / / edited by Petr Tichavský, Massoud Babaie-Zadeh, Olivier J.J. Michel, Nadège Thirion-Moreau |
Edizione | [1st ed. 2017.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
Descrizione fisica | 1 online resource (XVI, 576 p. 174 illus.) |
Disciplina | 621.3822 |
Collana | Theoretical Computer Science and General Issues |
Soggetto topico |
Pattern recognition systems
Computer vision Artificial intelligence Computer simulation Numerical analysis Computer networks Automated Pattern Recognition Computer Vision Artificial Intelligence Computer Modelling Numerical Analysis Computer Communication Networks |
ISBN | 3-319-53547-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Tensor Approaches -- Higher-Order Block Term Decomposition for Spatially Folded fMRI Data -- 1 Introduction -- 1.1 Notation -- 2 Tensorial fMRI Analysis -- 2.1 Canonical Polyadic Decomposition (CPD) -- 2.2 Tensor Probabilistic Independent Component Analysis (TPICA) -- 3 Block Term Decomposition (BTD) for fMRI -- 3.1 Uniqueness -- 4 Simulation Results -- 4.1 Simulation of a Perception Study -- 4.2 Multi-slice Simulation -- 5 Conclusions -- References -- Modeling Parallel Wiener-Hammerstein Systems Using Tensor Decomposition of Volterra Kernels -- 1 Introduction -- 2 Volterra Kernels, Tensors and Tensor Decomposition -- 2.1 The Volterra Model for Nonlinear Systems -- 2.2 From Polynomials to Tensors -- 2.3 Canonical Polyadic Decomposition -- 3 Parallel Wiener-Hammerstein as Tensor Decomposition -- 3.1 Wiener-Hammerstein as Structured Tensor Decomposition -- 3.2 Parallel Wiener-Hammerstein Structure -- 3.3 Coupled Tensor and Matrix Decompositions -- 4 Numerical Results -- 5 Conclusions -- References -- Fast Nonnegative Matrix Factorization and Completion Using Nesterov Iterations -- 1 Introduction -- 2 Standard NeNMF -- 3 Extending NeNMF to Missing Entries -- 3.1 Weigthed Extension of NeNMF -- 3.2 EM Extension of NeNMF -- 4 Performance of the Weighted NeNMF Extensions -- 5 Conclusion -- A Proof of Lemmas 1 and 2 -- References -- Blind Source Separation of Single Channel Mixture Using Tensorization and Tensor Diagonalization -- 1 Introduction -- 2 General Framework for BSS of Single Channel Mixture -- 3 Tensorization of Sinusoid Signals -- 3.1 Two-Way and Three-Way Foldings -- 3.2 Toeplitzation -- 4 Simulations -- 5 Conclusions -- A Appendix: Low-Rank Representation of the Sequence x(t) = tn -- References -- High-Resolution Subspace-Based Methods: Eigenvalue- or Eigenvector-Based Estimation?.
1 Introduction -- 2 Multilevel Hankel Matrices and Their Subspaces -- 2.1 Definition and Factorization -- 2.2 Shift Properties of Subspaces -- 3 ESPRIT-Type Algorithms for MH Matrices -- 3.1 N-D ESPRIT Algorithm -- 3.2 IMDF Algorithm -- 3.3 IMDF Based on Least Squares (IMDF LS) -- 4 Perturbation Analysis -- 4.1 Basic Expressions -- 4.2 IMDF Perturbations -- 4.3 IMDF LS Perturbations -- 4.4 Computing the First-Order Perturbation and Its Moments -- 5 Simulations -- 6 Conclusions -- References -- From Source Positions to Room Properties: Learning Methods for Audio Scene Geometry Estimation -- Speaker Tracking on Multiple-Manifolds with Distributed Microphones -- 1 Introduction -- 2 Problem Formulation -- 3 Multiple-Manifold Gaussian Process -- 4 Multiple-Manifold Speaker Tracking -- 5 Experimental Study -- 6 Conclusions -- References -- VAST: The Virtual Acoustic Space Traveler Dataset -- 1 Introduction -- 2 Dataset Design -- 2.1 General Principles -- 2.2 Room Simulation and Data Generation -- 2.3 Room Properties: Size and Surfaces -- 2.4 Reverberation Time -- 2.5 Source and Receiver Positions -- 2.6 Test Sets -- 3 Virtually Supervised Sound Source Localization -- 4 Conclusion -- References -- Sketching for Nearfield Acoustic Imaging of Heavy-Tailed Sources -- 1 Introduction -- 2 Mixture Model and -Stable Theory -- 2.1 Notation and Convolutive Model -- 2.2 Independent Isotropic -Stable Model for the Sources -- 2.3 The Levy Exponent and the Spatial Measure -- 3 Parameter Estimation -- 3.1 Sketching for the Levy Exponent -- 3.2 A Proposed NMF Algorithm to Determine -- 4 Evaluation -- 5 Conclusion -- References -- Acoustic DoA Estimation by One Unsophisticated Sensor -- 1 Introduction -- 2 Localization of Noise Sources -- 2.1 Geometrical Structure -- 2.2 Structure Quality -- 2.3 Conditions for Localization -- 3 Algorithms -- 3.1 Subspace Model. 3.2 Dictionary Model -- 4 Numerical Results -- 4.1 White Sources -- 4.2 Speech Sources -- 5 Conclusion -- References -- Acoustic Source Localization by Combination of Supervised Direction-of-Arrival Estimation with Disjoint Component Analysis -- 1 Introduction -- 2 Methods -- 2.1 Probabilistic Source Localization -- 2.2 Disjoint Component Analysis -- 2.3 Decomposition of Source Probability Map -- 2.4 Multi-channel Signal Enhancement -- 3 Experiments and Results -- 4 Summary and Discussion -- References -- Tensors and Audio -- An Initialization Method for Nonlinear Model Reduction Using the CP Decomposition -- 1 Introduction -- 2 Notations and Problem Statement -- 3 Finding an Appropriate Initialization -- 4 Simulations and Results -- 5 Case Study -- 6 Conclusion -- References -- Audio Zoom for Smartphones Based on Multiple Adaptive Beamformers -- 1 Introduction -- 2 Proposed Audio Zoom System -- 2.1 Target Sound Source Enhancement -- 2.2 Proposed Audio Zoom Effect Creation -- 3 Experiments -- 3.1 Experiment Setup -- 3.2 Result with Subjective Test -- 4 Conclusion -- References -- Complex Valued Robust Multidimensional SOBI -- 1 Introduction -- 2 Preliminaries -- 3 Algorithms -- 3.1 SOBI -- 3.2 Affine Equivariant SAM-SOBI -- 3.3 Multidimensional SOBI -- 3.4 Robust Multidimensional SOBI -- 4 Simulation Study -- 5 Conclusions -- References -- Ego Noise Reduction for Hose-Shaped Rescue Robot Combining Independent Low-Rank Matrix Analysis and Multichannel Noise Cancellation -- 1 Introduction -- 2 Hose-Shaped Rescue Robot and Ego Noise -- 2.1 Hose-Shaped Rescue Robot -- 2.2 Problem in Recording Speech -- 3 Overview of Independent Low-Rank Matrix Analysis -- 3.1 Formulation -- 3.2 Independent Low-Rank Matrix Analysis -- 4 Multichannel Noise Canceller -- 4.1 Conventional Method -- 4.2 Proposed Method -- 4.3 Flow of the Proposed Method -- 5 Experiment. 5.1 Conditions -- 5.2 Results -- 6 Conclusion -- References -- Some Theory on Non-negative Tucker Decomposition -- 1 Tensor Decomposition Models -- 1.1 Tucker Decompositions -- 1.2 Canonical Polyadic Decomposition -- 2 Propagating Non-negativity and Non-negative Rank Through NTD -- 2.1 Elements of Cone Theory -- 2.2 Working Hypotheses -- 2.3 Propagating the Non-negative Rank to the Core -- 2.4 Propagating Non-negativity to the Core -- 3 Simulations -- 3.1 Some Algorithms for NTD and NMF -- 3.2 Some Tests on the Outputs of Algorithms -- 4 Conclusion -- References -- A New Algorithm for Multimodal Soft Coupling -- 1 Introduction -- 2 Soft Coupling for NMF -- 2.1 NMF Model -- 2.2 Coupled NMF -- 3 The Proposed Algorithm -- 3.1 Update Rule for Updating H1 -- 3.2 Update Rule for Updating -- 4 Experimental Results -- 5 Conclusion -- References -- Adaptive Blind Separation of Instantaneous Linear Mixtures of Independent Sources -- 1 Introduction -- 2 Signal Model and Separation Performance Limits -- 3 Adaptive BSS Algorithms -- 3.1 Scaled Stochastic Natural Gradient Algorithm -- 3.2 Adaptive BGSEP -- 3.3 Adaptive BARBI -- 4 Experiments -- 5 Conclusion -- References -- Source Separation, Dereverberation and Noise Reduction Using LCMV Beamformer and Postfilter -- 1 Introduction -- 2 Problem Formulation -- 3 Optimal Multichannel Speaker Separation, Dereverberation and Noise Reduction -- 4 Estimation of the Late Reverberation PSD Matrix -- 4.1 Estimator Based on a Temporal Model -- 4.2 Estimator Based on a Spatial Model -- 5 Performance Evaluation -- 5.1 Setup -- 5.2 Results -- 6 Conclusions -- References -- Toward Rank Disaggregation: An Approach Based on Linear Programming and Latent Variable Analysis -- 1 Introduction -- 2 Rank Aggregation -- 2.1 Rank-Aggregation as an Optimization Problem -- 2.2 Criteria for Rank Aggregation. 2.3 Numerical Example: CAC 40 Ranking of the Top 10 French Companies -- 3 Towards Rank Disaggregation -- 3.1 Rank Disaggregation via a Multivariate Decomposition Approach -- 3.2 Numerical Experiment -- 4 Conclusion -- References -- A Proximal Approach for Nonnegative Tensor Decomposition -- 1 Introduction -- 2 Canonical Polyadic Decomposition of N-th Order Tensors -- 2.1 Model -- 2.2 Objective -- 3 Optimization Problem and Proximal Algorithm -- 3.1 Criterion Formulation, Assumptions and Properties -- 3.2 Proposed Algorithm -- 3.3 Criterion Choice: Related Gradient and Proximity Operators -- 4 Numerical Simulations: Application to 4-th Order CPD -- 5 Conclusion -- References -- Psychophysical Evaluation of Audio Source Separation Methods -- Abstract -- 1 Introduction -- 2 Method -- 3 Results: Analysis I - Psychophysical Correlation -- 4 Results: Analysis II - Comparison of Separation Methods -- 5 Conclusion and Discussion -- Acknowledgment -- References -- Audio Signal Processing -- On the Use of Latent Mixing Filters in Audio Source Separation -- 1 Introduction -- 2 Latent Mixing Filters and Estimation of Source Image -- 2.1 Principle -- 2.2 General Expression of the Source Image MMSE Estimator -- 2.3 The Gaussian Case -- 2.4 Inference of Source Image Using Metropolis Algorithm -- 3 Experiments -- 4 Conclusion -- References -- Discriminative Enhancement for Single Channel Audio Source Separation Using Deep Neural Networks -- 1 Introduction -- 2 Problem Formulation of Audio SCSS -- 3 DNNs for source separation and enhancement -- 3.1 Training DNN-A for Source Separation -- 3.2 Training DNN-B for Discriminative Enhancement -- 3.3 Testing DNN-A and DNN-B -- 4 Experiments and Discussion -- 5 Conclusion -- References -- Audiovisual Speech Separation Based on Independent Vector Analysis Using a Visual Voice Activity Detector -- 1 Introduction. 2 Mathematical Preliminaries. |
Record Nr. | UNINA-9910485010103321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|