Latent Variable Analysis and Signal Separation [electronic resource] : 12th International Conference, LVA/ICA 2015, Liberec, Czech Republic, August 25-28, 2015, Proceedings / edited by Emmanuel Vincent, Arie Yeredor, Zbyněk Koldovský, Petr Tichavský.
Material type:
TextSeries: Theoretical Computer Science and General Issues ; 9237 | Lecture Notes in Computer Science ; 9237Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Edition: 1st ed. 2015Description: XVI, 532 p. 128 illus. online resourceContent type: - text
- computer
- online resource
- 9783319224824
- Pattern recognition
- Optical data processing
- Computer simulation
- Algorithms
- Computer science—Mathematics
- Special purpose computers
- Pattern Recognition
- Image Processing and Computer Vision
- Simulation and Modeling
- Algorithm Analysis and Problem Complexity
- Discrete Mathematics in Computer Science
- Special Purpose and Application-Based Systems
- 006.4 23
- Q337.5
- TK7882.P3
E-BOOKS
| Home library | Call number | Materials specified | URL | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|---|
| IMSc Library | Link to resource | Available | EBK14325 |
Tensor-based methods for blind signal separation -- Deep neural networks for supervised speech separation/enhancment -- Joined analysis of multiple datasets, data fusion, and related topics -- Advances in nonlinear blind source separation -- Sparse and low rank modeling for acoustic signal processing.
This book constitutes the proceedings of the 12th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICS 2015, held in Liberec, Czech Republic, in August 2015. The 61 revised full papers presented – 29 accepted as oral presentations and 32 accepted as poster presentations – were carefully reviewed and selected from numerous submissions. Five special topics are addressed: tensor-based methods for blind signal separation; deep neural networks for supervised speech separation/enhancement; joined analysis of multiple datasets, data fusion, and related topics; advances in nonlinear blind source separation; sparse and low rank modeling for acoustic signal processing.
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