A Comparison of Serial & Parallel Particle Filters for Time Series Analysis
| dc.contributor.advisor | RubioRamírez, Juan F | |
| dc.contributor.author | Klemish, David | |
| dc.date.accessioned | 2014-05-14T19:22:49Z | |
| dc.date.available | 2014-05-14T19:22:49Z | |
| dc.date.issued | 2014 | |
| dc.department | Statistical and Economic Modeling | |
| dc.description.abstract | This paper discusses the application of parallel programming techniques to the estimation of hidden Markov models via the use of a particle filter. It highlights how the Thrust parallel programming language can be used to implement a particle filter in parallel. The impact of a parallel particle filter on the running times of three different models is investigated. For particle filters using a large number of particles, Thrust provides a speed-up of five to ten times over a serial C++ implementation, which is less than reported in other research. | |
| dc.identifier.uri | ||
| dc.subject | Statistics | |
| dc.title | A Comparison of Serial & Parallel Particle Filters for Time Series Analysis | |
| dc.type | Master's thesis |
Files
Original bundle
- Name:
- Klemish_duke_0066N_12444.pdf
- Size:
- 798.95 KB
- Format:
- Adobe Portable Document Format