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Subject / Keyword
- 10Particle filters
- 3Soft Sensor
- 2Ensemble Kalman filter
- 2Opponent modelling
- 1Agent modelling
- 1Artificial intelligence
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Author / Creator / Contributor
- 1Balakrishnapillai Chitralekha, Saneej
- 1Bard, Nolan DC
- 1Deng,Jing
- 1Dyson, Cameron
- 1Hajizadeh, Mohammad
- 1Hladky, Stephen Michael
Year
Item type
Departments
Supervisors
- 3Huang, Biao (Chemical and Materials Engineering)
- 1Bulitko, Vadim (Computing Science)
- 1Dr. Shah, Sirish (Chemical and Materials Engineering)
- 1Huang, Biao (Department of Chemical and Materials Engineering)
- 1Kouritzin, Mike (Mathematical and Statistical Sciences)
- 1Lipsett, Michael (Mechanical Engineering)
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Fall 2010
Estimation theory is a branch of statistics and probability that derives information about random variables based on known information. In process engineering, state estimation is used for a variety of purposes, such as: soft sensing, digital filter design, model predictive control and...
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Spring 2016
In this thesis, we first introduce two basic problems of filter, the nonlinear filtering and model selection problem. We show that both of them can be solved by the unnormalized filter approach. Then several web based particle filter algorithms will be discussed. We extend the resampled and...
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