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Latent Variable Analysis and Signal Separation

  • Kartonierter Einband
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This book constitutes the proceedings of the 9th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2010, held in St. Malo, France, in September 2010.
The 25 papers presented were carefully reviewed and selected from over hundred submissions. The papers collected in this volume demonstrate that the research activity in the field continues to gather theoreticians and practitioners, with contributions ranging range from abstract concepts to the most concrete and applicable questions and considerations. Speech and audio, as well as biomedical applications, continue to carry the mass of the considered applications. Unsurprisingly the concepts of sparsity and non-negativity, as well as tensor decompositions, have become predominant, reflecting the strongactivity on these themes in signal and image processing at large.

Speech and Audio Applications.- Blind Source Separation Based on Time-Frequency Sparseness in the Presence of Spatial Aliasing.- Adaptive Time-Domain Blind Separation of Speech Signals.- Time-Domain Blind Audio Source Separation Method Producing Separating Filters of Generalized Feedforward Structure.- Subband Blind Audio Source Separation Using a Time-Domain Algorithm and Tree-Structured QMF Filter Bank.- A General Modular Framework for Audio Source Separation.- Adaptive Segmentation and Separation of Determined Convolutive Mixtures under Dynamic Conditions.- Blind Speech Extraction Combining Generalized MMSE STSA Estimator and ICA-Based Noise and Speech Probability Density Function Estimations.- Blind Estimation of Locations and Time Offsets for Distributed Recording Devices.- Speech Separation via Parallel Factor Analysis of Cross-Frequency Covariance Tensor.- Under-Determined Reverberant Audio Source Separation Using Local Observed Covariance and Auditory-Motivated Time-Frequency Representation.- Crystal-MUSIC: Accurate Localization of Multiple Sources in Diffuse Noise Environments Using Crystal-Shaped Microphone Arrays.- Convolutive Signal Separation.- Consistent Wiener Filtering: Generalized Time-Frequency Masking Respecting Spectrogram Consistency.- Blind Separation of Convolutive Mixtures of Non-stationary Sources Using Joint Block Diagonalization in the Frequency Domain.- Single Microphone Blind Audio Source Separation Using EM-Kalman Filter and Short+Long Term AR Modeling.- The 2010 Signal Separation Evaluation Campaign (SiSEC2010).- The 2010 Signal Separation Evaluation Campaign (SiSEC2010): Audio Source Separation.- The 2010 Signal Separation Evaluation Campaign (SiSEC2010): Biomedical Source Separation.- Audio.- Use of Bimodal Coherence to Resolve Spectral Indeterminacy in Convolutive BSS.- Non-negative Hidden Markov Modeling of Audio with Application to Source Separation.- Nonnegative Matrix Factorization with Markov-Chained Bases for Modeling Time-Varying Patterns in Music Spectrograms.- An Experimental Evaluation of Wiener Filter Smoothing Techniques Applied to Under-Determined Audio Source Separation.- Auxiliary-Function-Based Independent Component Analysis for Super-Gaussian Sources.- Theory.- ICA Separability of Nonlinear Models with References: General Properties and Application to Heisenberg-Coupled Quantum States (Qubits).- Adaptive Underdetermined ICA for Handling an Unknown Number of Sources.- Independent Phase Analysis: Separating Phase-Locked Subspaces.- Second and Higher-Order Correlation Analysis of Multiple Multidimensional Variables by Joint Diagonalization.- Independent Component Analysis of Time/Position Varying Mixtures.- Random Pruning of Blockwise Stationary Mixtures for Online BSS.- Use of Prior Knowledge in a Non-Gaussian Method for Learning Linear Structural Equation Models.- A New Performance Index for ICA: Properties, Computation and Asymptotic Analysis.- Blind Operation of a Recurrent Neural Network for Linear-Quadratic Source Separation: Fixed Points, Stabilization and Adaptation Scheme.- Statistical Model of Speech Signals Based on Composite Autoregressive System with Application to Blind Source Separation.- Information-Theoretic Model Selection for Independent Components.- Blind Source Separation of Overdetermined Linear-Quadratic Mixtures.- Constrained Complex-Valued ICA without Permutation Ambiguity Based on Negentropy Maximization.- Time Series Causality Inference Using Echo State Networks.- Complex Blind Source Separation via Simultaneous Strong Uncorrelating Transform.- A General Approach for Robustification of ICA Algorithms.- Strong Sub- and Super-Gaussianity.- Telecom.- Hybrid Channel Estimation Strategy for MIMO Systems with Decision Feedback Equalizer.- An Alternating Minimization Method for Sparse Channel Estimation.- A Method for Filter Equalization in Convolutive Blind Source Separation.- Cancellation of Nonlinear Inter-Carrier Interference in OFDM Systems with Nonlinear Power-Amplifiers.- Tensor Factorizations.- Probabilistic Latent Tensor Factorization.- Nonorthogonal Independent Vector Analysis Using Multivariate Gaussian Model.- Deterministic Blind Separation of Sources Having Different Symbol Rates Using Tensor-Based Parallel Deflation.- Second Order Subspace Analysis and Simple Decompositions.- Sensitivity of Joint Approximate Diagonalization in FD BSS.- Sparsity I.- Blind Compressed Sensing: Theory.- Blind Extraction of the Sparsest Component.- Blind Extraction of Intermittent Sources.- Dictionary Learning for Sparse Representations: A Pareto Curve Root Finding Approach.- SMALLbox - An Evaluation Framework for Sparse Representations and Dictionary Learning Algorithms.- Sparsity; Biomedical Applications.- Fast Block-Sparse Decomposition Based on SL0.- Second-Order Source Separation Based on Prior Knowledge Realized in a Graph Model.- Noise Adjusted PCA for Finding the Subspace of Evoked Dependent Signals from MEG Data.- Binary Sparse Coding.- A Multichannel Spatial Compressed Sensing Approach for Direction of Arrival Estimation.- Robust Second-Order Source Separation Identifies Experimental Responses in Biomedical Imaging.- Decomposition of EEG Signals for Multichannel Neural Activity Analysis in Animal Experiments.- Non-negativity; Image Processing Applications.- Using Non-Negative Matrix Factorization for Removing Show-Through.- Nonlinear Band Expansion and 3D Nonnegative Tensor Factorization for Blind Decomposition of Magnetic Resonance Image of the Brain.- Informed Source Separation Using Latent Components.- Non-stationary t-Distribution Prior for Image Source Separation from Blurred Observations.- Automatic Rank Determination in Projective Nonnegative Matrix Factorization.- Non-negative Independent Component Analysis Algorithm Based on 2D Givens Rotations and a Newton Optimization.- A New Geometrical BSS Approach for Non Negative Sources.- Dependent Component Analysis for Cosmology: A Case Study.- Tensors; Joint Diagonalization.- A Time-Frequency Technique for Blind Separation and Localization of Pure Delayed Sources.- Joint Eigenvalue Decomposition Using Polar Matrix Factorization.- Joint SVD and Its Application to Factorization Method.- Sparsity II.- Double Sparsity: Towards Blind Estimation of Multiple Channels.- Adaptive and Non-adaptive ISI Sparse Channel Estimation Based on SL0 and Its Application in ML Sequence-by-Sequence Equalization.- Biomedical Applications.- Extraction of Foetal Contribution to ECG Recordings Using Cyclostationarity-Based Source Separation Method.- Common SpatioTemporal Pattern Analysis.- Recovering Spikes from Noisy Neuronal Calcium Signals via Structured Sparse Approximation.- Semi-nonnegative Independent Component Analysis: The (3,4)-SENICAexp Method.- Classifying Healthy Children and Children with Attention Deficit through Features Derived from Sparse and Nonnegative Tensor Factorization Using Event-Related Potential.- Emerging Topics.- Riemannian Geometry Applied to BCI Classification.- Separating Reflections from a Single Image Using Spatial Smoothness and Structure Information.- ICA over Finite Fields.


Titel: Latent Variable Analysis and Signal Separation
Untertitel: 9th International Conference, LVA/ICA 2010, St. Malo, France, September 27-30, 2010, Proceedings
EAN: 9783642159947
ISBN: 978-3-642-15994-7
Format: Kartonierter Einband
Herausgeber: Springer, Berlin
Genre: Informatik
Anzahl Seiten: 655
Gewicht: 943g
Größe: H241mm x B161mm x T28mm
Jahr: 2011
Untertitel: Englisch
Auflage: 2010

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