Name
Abstract | ||
|---|---|---|
The fitting of Markov arrival processes (MAPs) with the expectation–maximization (EM) algorithm is a computationally demanding task. There are attempts in the literature to reduce the computational complexity by introducing special MAP structures instead of the general representation. Another possibility to improve the efficiency of MAP fitting is to reformulate the inherently serial classical EM algorithm to exploit modern, massively parallel hardware architectures. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.peva.2018.05.001 | Performance Evaluation |
Keywords | Field | DocType |
Markov arrival process,Traffic model fitting,EM algorithm,Parallel computation,GPU | Graphics,Computer science,Massively parallel,Expectation–maximization algorithm,Parallel algorithm,Erlang (programming language),Markov chain,Algorithm,Real-time computing,Hidden Markov model,Computational complexity theory | Journal |
Volume | ISSN | Citations |
123 | 0166-5316 | 0 |
PageRank | References | Authors |
0.34 | 13 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mindaugas Brazenas | 1 | 2 | 0.74 |
| Gábor Horváth | 2 | 210 | 35.47 |
| Miklós Telek | 3 | 922 | 102.56 |