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- 18Particle filters
- 2Bayesian Model Selection
- 2Branching Process
- 2Central Limit Theorem
- 2Ensemble Kalman filter
- 2Law of large numbers
- 7Kouritzin, Michael
- 2Wu, Biao
- 1Balakrishnapillai Chitralekha, Saneej
- 1Blount, Douglas
- 1Hajizadeh, Mohammad
We introduce two kinds of particle filters, one is weighted particle filter and the other is resampling particle filter. We prove the Strong Law of Large Numbers and Central Limit Theorem for both particle filters. Then, we show that the resampling particle filter is better than the weighted one.
The classical particle filter, introduced in 1993, approximates the normalized filter directly. It has two defiencies, over resampling and the inability to distinguish models, the former of which was overcome but the later is fundamental. Conversely, the weighted particle filter, motivated by the...
A hybrid weighted/interacting particle filter, the selectively resampling particle (SERP) filter, is used to detect and track an unknown number of independent targets on a one-dimensional \"racetrack\" domain. The targets evolve in a nonlinear manner. The observations model a sensor positioned...
The development of fast and efficient computer hardware technology has resulted in the rapid development of numerous computational software tools for making statistical inferences. The computational algorithms, which are the backbone of these tools, originate from distinct areas in science,...
The main area of research delineated in this thesis provides instances when Computer vision based technology has shown tremendous productivity gains in the Oil sands industry in Fort McMurray, Alberta, Canada. Specifically, the interface between Bitumen-froth (crude oil) and the Middlings (Sand)...
Military tanks, cargo or troop carriers, missile carriers or rocket launchers often hide themselves from detection in the forests. This plagues the detection problem of locating these hidden targets. An electro-optic camera mounted on a surveillance aircraft or unmanned aerial vehicle is used to...
Classical fault detection methods do not completely satisfy the reliability requirement for complex and highly nonlinear stochastic systems. One solution to this problem is to use more advances fault detection methods such as multiple models to simulate system in different operating...
Target Obscuration, including foliage or building obscuration of ground targets and landscape or horizon obscuration of airborne targets, plagues many real world filtering problems. In particular, ground moving target identification Doppler radar, mounted on a surveillance aircraft or unattended...
Herein, we consider direct Markov chain approximations to the Duncan–Mortensen–Zakai equations for nonlinear filtering problems on regular, bounded domains. For clarity of presentation, we restrict our attention to reflecting diffusion signals with symmetrizable generators. Our Markov chains are...
Limitations of measurement techniques and increasingly complex chemical process render difficulties in obtaining certain critical process variables. The hardware sensor reading may have an obvious bias compared with the real value. Off-line laboratory analysis with high accuracy can only be...