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Nonlinear Filtering and Optimal Phase Tracking
This book offers an analytical rather than measure-theoretical approach to the derivation of the partial differential equations of nonlinear filtering theory. The basis for this approach is the discrete numerical scheme used in Monte-Carlo simulations of stochastic differential equations and Wiene...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Springer US : Imprint: Springer,
2012.
|
| Edición: | 1st ed. 2012. |
| Colección: | Applied Mathematical Sciences,
180 |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 001 | 978-1-4614-0487-3 | ||
| 003 | DE-He213 | ||
| 005 | 20220116220639.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 111114s2012 xxu| s |||| 0|eng d | ||
| 020 | |a 9781461404873 |9 978-1-4614-0487-3 | ||
| 024 | 7 | |a 10.1007/978-1-4614-0487-3 |2 doi | |
| 050 | 4 | |a QA273.A1-274.9 | |
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| 100 | 1 | |a Schuss, Zeev. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Nonlinear Filtering and Optimal Phase Tracking |h [electronic resource] / |c by Zeev Schuss. |
| 250 | |a 1st ed. 2012. | ||
| 264 | 1 | |a New York, NY : |b Springer US : |b Imprint: Springer, |c 2012. | |
| 300 | |a XVIII, 262 p. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Applied Mathematical Sciences, |x 2196-968X ; |v 180 | |
| 505 | 0 | |a Diffusion and Stochastic Differential Equations -- Euler's Simulation Scheme and Wiener's Measure -- Nonlinear Filtering and Smoothing of Diffusions -- Small Noise Analysis of Zakai's Equation -- Loss of Lock in Phase Trackers -- Loss of Lock in RADAR and Synchronization -- Phase Tracking with Optimal Lock Time -- Bibliography -- Index. | |
| 520 | |a This book offers an analytical rather than measure-theoretical approach to the derivation of the partial differential equations of nonlinear filtering theory. The basis for this approach is the discrete numerical scheme used in Monte-Carlo simulations of stochastic differential equations and Wiener's associated path integral representation of the transition probability density. Furthermore, it presents analytical methods for constructing asymptotic approximations to their solution and for synthesizing asymptotically optimal filters. It also offers a new approach to the phase tracking problem, based on optimizing the mean time to loss of lock. The book is based on lecture notes from a one-semester special topics course on stochastic processes and their applications that the author taught many times to graduate students of mathematics, applied mathematics, physics, chemistry, computer science, electrical engineering, and other disciplines. The book contains exercises and worked-out examples aimed at illustrating the methods of mathematical modeling and performance analysis of phase trackers. | ||
| 650 | 0 | |a Probabilities. | |
| 650 | 0 | |a Mathematical physics. | |
| 650 | 0 | |a Differential equations. | |
| 650 | 1 | 4 | |a Probability Theory. |
| 650 | 2 | 4 | |a Theoretical, Mathematical and Computational Physics. |
| 650 | 2 | 4 | |a Differential Equations. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9781489973818 |
| 776 | 0 | 8 | |i Printed edition: |z 9781461404880 |
| 776 | 0 | 8 | |i Printed edition: |z 9781461404866 |
| 830 | 0 | |a Applied Mathematical Sciences, |x 2196-968X ; |v 180 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-1-4614-0487-3 |z Texto Completo |
| 912 | |a ZDB-2-SMA | ||
| 912 | |a ZDB-2-SXMS | ||
| 950 | |a Mathematics and Statistics (SpringerNature-11649) | ||
| 950 | |a Mathematics and Statistics (R0) (SpringerNature-43713) | ||