Dynamic Bayesian Networks - Fundamentals and Applications
Fouad Sabry
Verlag: One Billion Knowledgeable
Beschreibung
What Is Dynamic Bayesian Networks A Bayesian network (BN) is referred to as a Dynamic Bayesian Network (DBN), which is a network that ties variables to each other throughout consecutive time steps. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Dynamic Bayesian Network Chapter 2: Bayesian Network Chapter 3: Hidden Markov Model Chapter 4: Graphical Model Chapter 5: Recursive Bayesian Estimation Chapter 6: Time Series Chapter 7: Statistical Relational Learning Chapter 8: Bayesian Programming Chapter 9: Switching Kalman Filter Chapter 10: Dependency Network (Graphical Model) (II) Answering the public top questions about dynamic bayesian networks. (III) Real world examples for the usage of dynamic bayesian networks in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of dynamic bayesian networks' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of dynamic bayesian networks.
