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Hardcover - 9781461463153
149,79 €
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Beschreibung
This book discusses state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and nonlinear or stochastic filtering. The class of solutions presented in this book is based on the Monte Carlo statistical method. Although the resulting algorithms, known as particle filters, have been around for more than a decade, the recent theoretical developments of sequential Bayesian estimation in the framework of random set theory have provided new opportunities which are not widely known and are covered in this book. This book is ideal for graduate students, researchers, scientists and engineers interested in Bayesian estimation.
Details
| Verlag | Springer US |
| Ersterscheinung | 22. Mai 2015 |
| Maße | 23.5 cm x 15.5 cm |
| Gewicht | 295 Gramm |
| Format | Softcover |
| ISBN-13 | 9781489988843 |
| Auflage | 2013 |
| Seiten | 174 |
Schlagwörter
Artificial Intelligence, Computational Intelligence, Digitale Signalverarbeitung (DSP), Elektronik, Künstliche Intelligenz, Mathematical Applications in Computer Science, Mathematik für Informatiker, Probability and Statistics in Computer Science, Signal - Speech and Image Processing, Theoretische Informatik, Wahrscheinlichkeitsrechnung und Statistik
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