Bayesian signal processing classical, modern, and particle filtering methods
New Bayesian approach helps you solve tough problems in signal processing with ease Signal processing is based on this fundamental concept-the extraction of critical information from noisy, uncertain data. Most techniques rely on underlying Gaussian assumptions for a solution, but what happens when...
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, N.J. :
Wiley
c2009.
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| Edición: | 1st edition |
| Colección: | Wiley series in adaptive and learning systems for signal processing, communications, and control
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627991606719 |
Tabla de Contenidos:
- BAYESIAN SIGNAL PROCESSING; CONTENTS; Preface; Acknowledgments; 1 Introduction; 2 Bayesian Estimation; 3 Simulation-Based Bayesian Methods; 4 State-Space Models for Bayesian Processing; 5 Classical Bayesian State-Space Processors; 6 Modern Bayesian State-Space Processors; 7 Particle-Based Bayesian State-Space Processors; 8 Joint Bayesian State/Parametric Processors; 9 Discrete Hidden Markov Model Bayesian Processors; 10 Bayesian Processors for Physics-Based Applications; Appendix A Probability & Statistics Overview; Index
