Name
Abstract | ||
|---|---|---|
We present an online method for joint state and parameter estimation in jump Markov non-linear systems (JMNLS). State inference is enabled via the use of particle filters which makes the method applicable to a wide range of non-linear models. To exploit the inherent structure of JMNLS, we design a Rao-Blackwellized particle filter (RBPF) where the discrete mode is marginalized out analytically. This results in an efficient implementation of the algorithm and reduces the estimation error variance. The proposed RBPF is then used to compute, recursively in time, smoothed estimates of complete data sufficient statistics. Together with the online expectation maximization algorithm, this enables recursive identification of unknown model parameters including the transition probability matrix. The method is also applicable to online identification of jump Markov linear systems(JMLS). The performance of the method is illustrated in simulations and on a localization problem in wireless networks using real data. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TSP.2014.2385039 | Signal Processing, IEEE Transactions |
Keywords | Field | DocType |
markov processes,expectation-maximisation algorithm,matrix algebra,particle filtering (numerical methods),recursive estimation,jmnls,rbpf,rao-blackwellized particle filter,discrete mode,estimation error variance reduction,joint state and parameter estimation,jump markov linear systems,jump markov nonlinear system,localization problem,online expectation maximization algorithm,particle filters,recursive identification,recursive maximum likelihood identification,state inference,transition probability matrix,adaptive filtering,rao-blackwellization,expectation maximization,identification,jump markov systems,parameter estimation,particle filter,transition probability estimation,hidden markov models,computational modeling | Mathematical optimization,Markov process,Markov property,Forward algorithm,Markov model,Markov chain,Recursive Bayesian estimation,Variable-order Markov model,Markov kernel,Mathematics | Journal |
Volume | Issue | ISSN |
63 | 3 | 1053-587X |
Citations | PageRank | References |
11 | 0.57 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emre Özkan | 1 | 94 | 10.54 |
| Fredrik Lindsten | 2 | 168 | 21.08 |
| Carsten Fritsche | 3 | 157 | 14.72 |
| Fredrik Gustafsson | 4 | 2287 | 281.33 |