Name
Title | ||
|---|---|---|
Hybrid Metaheuristic Approaches to the Expectation Maximization for Estimation of the Hidden Markov Model for Signal Modeling. |
Abstract | ||
|---|---|---|
The expectation maximization (EM) is the standard training algorithm for hidden Markov model (HMM). However, EM faces a local convergence problem in HMM estimation. This paper attempts to overcome this problem of EM and proposes hybrid metaheuristic approaches to EM for HMM. In our earlier research, a hybrid of a constraint-based evolutionary learning approach to EM (CEL-EM) improved HMM estimatio... |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TCYB.2014.2308917 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Hidden Markov models,Estimation,Stochastic processes,Training,Convergence,Simulated annealing,Standards | Simulated annealing,TIMIT,Mathematical optimization,Expectation–maximization algorithm,Markov model,Artificial intelligence,Variable-order Markov model,Local convergence,Hidden Markov model,Machine learning,Mathematics,Metaheuristic | Journal |
Volume | Issue | ISSN |
44 | 10 | 2168-2267 |
Citations | PageRank | References |
2 | 0.36 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Md. Shamsul Huda | 1 | 71 | 9.65 |
| John Yearwood | 2 | 268 | 32.05 |
| Roberto Togneri | 3 | 814 | 48.33 |