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Sampling Theory, a Renaissance Compressive Sensing and Other Developments /
Reconstructing or approximating objects from seemingly incomplete information is a frequent challenge in mathematics, science, and engineering. A multitude of tools designed to recover hidden information are based on Shannon's classical sampling theorem, a central pillar of Sampling Theory. The...
| Clasificación: | Libro Electrónico |
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| Autor Corporativo: | |
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| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Birkhäuser,
2015.
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| Edición: | 1st ed. 2015. |
| Colección: | Applied and Numerical Harmonic Analysis,
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| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- Part I: Sparsity Models
- Estimation in High Dimensions: A Geometric Perspective
- Convex Recovery of a Structured Signal from Independent Random Linear Measurements
- Low Complexity Regularization of Linear Inverse Problems
- Part II: Frames with Benefits
- Noise-shaping Quantization Methods for Frame-based and Compressive Sampling Systems
- Fourier Operations in Applied Harmonic Analysis.- The Fundamentals of Spectral Tetris Frame Constructions
- Part III: Bandlimitation Recast
- System Approximation and Generalized Measurements in Modern Sampling Theory
- Entire Functions in Generalized Bernstein Spaces and Their Growth Behavior
- Sampling and Geometry
- A Sheaf-theoretic Perspective on Sampling
- Part IV: Solutions of Parametric PDEs
- How to Best Sample a Solution Manifold?
- On the Stability of Polynomial Interpolation using Hierarchical Sampling
- Part V: Implementation
- OperA: Operator-based Annihilation for Finite-Rate-of-Innovation Signal Sampling
- Digital Adaptive Calibration of Data Converters using Independent Component Analysis.