Name
Abstract | ||
|---|---|---|
The purpose of this paper is threefold. First, it briefly introduces basic Bayesian techniques with emphasis on present applications in sensor networks. Second, it reviews modern Bayesian simulation methods, thereby providing an introduction to the main building blocks of the advanced Markov chain Monte Carlo and Sequential Monte Carlo methods. Lastly, it discusses new interesting research horizons. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-14654-1_40 | WASA |
Keywords | Field | DocType |
new interesting research horizon,main building block,modern bayesian simulation method,present application,basic bayesian technique,sequential monte carlo method,sensor network,advanced markov chain,monte carlo,sensor networks,monte carlo method,markov chain monte carlo,monte carlo methods | Monte Carlo method in statistical physics,Monte Carlo method,Markov chain Monte Carlo,Computer science,Particle filter,Hybrid Monte Carlo,Monte Carlo integration,Artificial intelligence,Parallel tempering,Monte Carlo molecular modeling,Machine learning | Conference |
Volume | ISSN | ISBN |
6221 | 0302-9743 | 3-642-14653-8 |
Citations | PageRank | References |
0 | 0.34 | 13 |
Authors | ||
1 | ||