Name
Abstract | ||
|---|---|---|
The classical Viterbi algorithm (ML sequence estimation) can be computed using a forward-backward structure, similar to that of the classical hidden Markov model forward-backward algorithm (MAP state estimation). This similarity is exploited to develop a hybrid algorithm which provides a mathematical connection between ML sequence estimation and MAP state estimation |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1109/18.737542 | IEEE Transactions on Information Theory |
Keywords | Field | DocType |
hybrid algorithm,soft output,forward-backward structure,mathematical connection,map state estimation,forward-backward algorithm,map sequence estimation,classical hidden markov model,classical viterbi algorithm,ml sequence estimation,information theory,forward backward algorithm,hidden markov models,distributed computing,decoding,indexing terms,adaptive systems,viterbi algorithm,maximum likelihood estimation,structural similarity,hidden markov model,robustness,maximum likelihood sequence estimation | Hybrid algorithm,Forward algorithm,Pattern recognition,Computer science,Soft output Viterbi algorithm,Robustness (computer science),Artificial intelligence,Hidden Markov model,Maximum likelihood sequence estimation,Iterative Viterbi decoding,Viterbi algorithm | Journal |
Volume | Issue | ISSN |
44 | 7 | 0018-9448 |
Citations | PageRank | References |
7 | 0.86 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| G. D. Brushe | 1 | 34 | 5.55 |
| Robert Mahony | 2 | 23 | 5.69 |
| J. B. Moore | 3 | 12 | 1.81 |