Title Adaptive identification of acoustic multichannel systems using sparse representations / Karim Helwani

Published Cham : Springer, [2014] ©2015

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Description 1 online resource (xiv, 113 pages) : illustrations (some color) Series T-Labs Series in Telecommunication Services, 2192-2810 T-labs series in telecommunication services, 2192-2810 Contents Acknowledgments; Contents; Abbreviations and Symbols; Abstract; 1 Introduction; 1.1 Problem Statement; 1.2 State of the Art in High-Resolution Spatial Sound Reproduction; 1.3 State of the Art in High-Resolution Spatial Sound Analysis; 1.4 State of the Art in Adaptive Filtering; 1.4.1 Frequency-Domain Adaptive Filtering; 1.4.2 Proportionate Adaptive Filtering Algorithms; 1.4.3 Model-Based Adaptive Filtering and Post-Processing; 1.4.4 Convergence Enhancement for Stereo Acoustic Echo Cancellation by a Preprocessing Stage; 1.5 Overview of This Book; References Part ITheoretical Multichannel SystemIdentification2 Fundamentals of Adaptive Filter Theory; 2.1 Signal and System Model; 2.1.1 Standard Representation; 2.1.2 Compact Representation; 2.2 Optimal System Identification in Least-Squares Sense; 2.2.1 The Wiener -- Hopf Equation; 2.2.2 Derivation of Iterative Estimation Approaches; References; 3 Spatio-Temporal Regularized Recursive Least Squares Algorithm; 3.1 Regularization from a Probabilistic Point of View; 3.2 Structured Regularization; 3.3 ellp, q-norm Constrained Adaptive Filtering; 3.4 Discussion of Special Cases 3.4.1 Multichannel Sparse Adaptive Filtering3.4.2 Efficient Computation of the Regularized Inverse; 3.5 Ill-Conditioning in Multichannel Adaptive Filtering and Sparseness Constraint; 3.6 Experiments; References; 4 Sparse Representation of Multichannel Acoustic Systems; 4.1 System Sparsity; 4.1.1 Prior Knowledge from Physics; 4.1.2 Incorporating the Prior Knowledge on Spatially Discrete Acoustic Systems; 4.1.3 Eigenspace Adaptive Filtering; 4.2 Signal Sparsity; 4.3 Source-Domain Estimation; 4.3.1 Permutation Problem; 4.4 Efficient System Identification in the Source Domain; 4.4.1 Algorithm 4.4.2 Adaptation Control4.5 Experiments; References; 5 Unique System Identification from Projections; 5.1 Generic Spatially Transformed Adaptive Filtering for Ill-Conditioned Problems; 5.2 System Eigenspace Estimation; 5.2.1 Validity of the Estimated Eigenspace; 5.2.2 Adaptation Control; 5.3 Experimental Results; 5.3.1 Performance Measures; 5.3.2 Simulation; References; Part IIPractical Aspects; 6 Geometrical Constraints; 6.1 Synthesis of Sound Fields; 6.2 Analytical Solution to the Synthesis of Sound Figures; 6.2.1 Mathematical Problem Formulation 6.2.2 Conditions for the Synthesis of Sound Figures6.3 Synthesis of Closed Zones of Quiet; 6.3.1 Approximation of the Driving Functions Based on the Kirchhoff -- Helmholtz Integral; 6.3.2 Analytical Derivation of the Driving Functions; 6.4 Linear Distribution of Secondary Sources as Limiting Case of a Closed Distribution; 6.4.1 Linear Secondary Source Distributions; 6.4.2 Arrays with Convex Geometries as Linear Arrays; 6.4.3 Example of the Synthesis of Sound Figures on a Line Using Linear Arrays; 6.4.4 Sound Figures as Functions on Two-Dimensional Manifolds Summary This book treats the topic of extending the adaptive filtering theory in the context of massive multichannel systems by taking into account a priori knowledge of the underlying system or signal. The starting point is exploiting the sparseness in acoustic multichannel system in order to solve the non-uniqueness problem with an efficient algorithm for adaptive filtering that does not require any modification of the loudspeaker signals. The book discusses in detail the?derivation of general sparse representations of acoustic MIMO systems?in signal or system dependent transform domains.?Efficient a Analysis engineering beeldverwerking image processing spraak speech geluidsleer acoustics datacommunicatie data communication Engineering (General) Techniek (algemeen) Bibliography Includes bibliographical references Notes Online resource; title from PDF title page (SpringerLink, viewed August 6, 2014) Subject Adaptive signal processing. MIMO systems. TECHNOLOGY & ENGINEERING -- Mechanical. Adaptive signal processing MIMO systems Form Electronic book ISBN 9783319089546 3319089544 3319089536 9783319089539

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