| Description |
1 online resource (xii, 225 pages) : illustrations (some color) |
| Series |
Lecture notes in electrical engineering ; v. 3 |
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Lecture notes in electrical engineering ; v. 3.
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| Contents |
Account for Random Microstructure in Multiscale Models -- Multiscale Modeling of Tensile Failure in Fiber-Reinforced Composites -- Adaptive Concurrent Multi-Level Model for Multiscale Analysis of Composite Materials Including Damage -- Multiscale and Multi-Level Modeling of Composites -- A Micro-Mechanics-Based Notion of Stress for use in the Determination of Continuum-Level Mechanical Properties via Molecular Dynamics -- Multiscale Modeling and Simulation of Deformation in Nanoscale Metallic Multilayered Composites -- Multiscale Modeling of Composites Using Analytical Methods -- Nested Nonlinear Multiscale Frameworks for the Analysis of Thick-Section Composite Materials and Structures -- Predicting Thermooxidative Degradation and Performance of High-Temperature Polymer Matrix Composites -- Modeling of Stiffness, Strength, and Structure-Property Relationship in Crosslinked Silica Aerogel -- Multiscale Modeling of the Evolution of Damage in Heterogeneous Viscoelastic Solids -- Multiscale Modeling for Damage Analysis -- Hierarchical Modeling of Deformation of Materials from the Atomic to the Continuum Scale |
| Summary |
Time-Domain Beamforming and Blind Source Separation addresses the problem of separating spontaneous multi-party speech by way of microphone arrays (beamformers) and adaptive signal processing techniques. While existing techniques require a Double-Talk Detector (DTD) that interrupts the adaptation when the target is active, the described method addresses the separation problem using continuous, uninterrupted adaptive algorithms. With this approach, algorithm development is much simpler since no detection mechanism needs to be designed and needs no threshold to be tuned. Also, performance can be improved due to the adaptation during periods of double-talk. The authors use two techniques to achieve these results: implicit beamforming, which requires the position of the target speaker to be known; and time-domain blind-source separation (BSS), which exploits second-order statistics of the source signals. In combination, beamforming and BSS can be used to develop novel algorithms. Emphasis is placed on the development of an algorithm that combines the benefits of both approaches. The book presents experimental results obtained with real in-car microphone recordings involving simultaneous speech of the driver and the co-driver. In addition, experiments with background noise have been carried out in order to assess the robustness of the considered methods in noisy conditions |
| Bibliography |
Includes bibliographical references (pages 215-221) and index |
| Notes |
Print version record |
| Subject |
Blind source separation.
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Speech processing systems
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Mobile communication systems.
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TECHNOLOGY & ENGINEERING -- Radio.
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TECHNOLOGY & ENGINEERING -- Mobile & Wireless Communications.
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Ingénierie.
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Blind source separation
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Mobile communication systems
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Speech processing systems
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| Form |
Electronic book
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| Author |
Minker, Wolfgang.
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| ISBN |
9780387688367 |
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0387688366 |
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0387688358 |
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9780387688350 |
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