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Degree: MS

You searched for subject:( Particle Filter). Showing records 1 – 30 of 46 total matches.

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University of Alberta

1. Ye, Zi. A Discrete-time Particle Filter and Central Limit Theorem.

Degree: MS, Department of Mathematical and Statistical Sciences, 2013, University of Alberta

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.

Subjects/Keywords: Central Limit Theorem; Particle Filter

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APA (6th Edition):

Ye, Z. (2013). A Discrete-time Particle Filter and Central Limit Theorem. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/bz60cx09v

Chicago Manual of Style (16th Edition):

Ye, Zi. “A Discrete-time Particle Filter and Central Limit Theorem.” 2013. Masters Thesis, University of Alberta. Accessed March 24, 2019. https://era.library.ualberta.ca/files/bz60cx09v.

MLA Handbook (7th Edition):

Ye, Zi. “A Discrete-time Particle Filter and Central Limit Theorem.” 2013. Web. 24 Mar 2019.

Vancouver:

Ye Z. A Discrete-time Particle Filter and Central Limit Theorem. [Internet] [Masters thesis]. University of Alberta; 2013. [cited 2019 Mar 24]. Available from: https://era.library.ualberta.ca/files/bz60cx09v.

Council of Science Editors:

Ye Z. A Discrete-time Particle Filter and Central Limit Theorem. [Masters Thesis]. University of Alberta; 2013. Available from: https://era.library.ualberta.ca/files/bz60cx09v


University of Alberta

2. Wang, Xingpu. Web Based Particle Filters.

Degree: MS, Department of Mathematical and Statistical Sciences, 2015, University of Alberta

 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… (more)

Subjects/Keywords: Branching; Resample; Bayes Inference; Particle Filter

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APA (6th Edition):

Wang, X. (2015). Web Based Particle Filters. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/c6969z0831

Chicago Manual of Style (16th Edition):

Wang, Xingpu. “Web Based Particle Filters.” 2015. Masters Thesis, University of Alberta. Accessed March 24, 2019. https://era.library.ualberta.ca/files/c6969z0831.

MLA Handbook (7th Edition):

Wang, Xingpu. “Web Based Particle Filters.” 2015. Web. 24 Mar 2019.

Vancouver:

Wang X. Web Based Particle Filters. [Internet] [Masters thesis]. University of Alberta; 2015. [cited 2019 Mar 24]. Available from: https://era.library.ualberta.ca/files/c6969z0831.

Council of Science Editors:

Wang X. Web Based Particle Filters. [Masters Thesis]. University of Alberta; 2015. Available from: https://era.library.ualberta.ca/files/c6969z0831


University of Alberta

3. Deng,Jing. Modeling and Development of Soft Sensors with Particle Filtering Approach.

Degree: MS, Department of Chemical and Materials Engineering, 2012, University of Alberta

 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… (more)

Subjects/Keywords: EM algorithm; Particle Filter; Soft Sensor

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APA (6th Edition):

Deng,Jing. (2012). Modeling and Development of Soft Sensors with Particle Filtering Approach. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/k643b130g

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

Deng,Jing. “Modeling and Development of Soft Sensors with Particle Filtering Approach.” 2012. Masters Thesis, University of Alberta. Accessed March 24, 2019. https://era.library.ualberta.ca/files/k643b130g.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

Deng,Jing. “Modeling and Development of Soft Sensors with Particle Filtering Approach.” 2012. Web. 24 Mar 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

Deng,Jing. Modeling and Development of Soft Sensors with Particle Filtering Approach. [Internet] [Masters thesis]. University of Alberta; 2012. [cited 2019 Mar 24]. Available from: https://era.library.ualberta.ca/files/k643b130g.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

Deng,Jing. Modeling and Development of Soft Sensors with Particle Filtering Approach. [Masters Thesis]. University of Alberta; 2012. Available from: https://era.library.ualberta.ca/files/k643b130g

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


Georgia Tech

4. Leonard, Andrew. Vehicle tracking using ultra-wideband radar.

Degree: MS, Mechanical Engineering, 2016, Georgia Tech

 In this thesis a vehicle tracking problem using an ultra-wideband radar sensor is considered. Prior research is heavily focused on specific applications, such as highway… (more)

Subjects/Keywords: Vehicle tracking; Ultra-wideband; Radar; Particle filter

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APA (6th Edition):

Leonard, A. (2016). Vehicle tracking using ultra-wideband radar. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56265

Chicago Manual of Style (16th Edition):

Leonard, Andrew. “Vehicle tracking using ultra-wideband radar.” 2016. Masters Thesis, Georgia Tech. Accessed March 24, 2019. http://hdl.handle.net/1853/56265.

MLA Handbook (7th Edition):

Leonard, Andrew. “Vehicle tracking using ultra-wideband radar.” 2016. Web. 24 Mar 2019.

Vancouver:

Leonard A. Vehicle tracking using ultra-wideband radar. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2019 Mar 24]. Available from: http://hdl.handle.net/1853/56265.

Council of Science Editors:

Leonard A. Vehicle tracking using ultra-wideband radar. [Masters Thesis]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56265

5. Marathe, Kedar Pramodan. An Adaptive Nested Particle Filter with Advanced Weighting to handle localization and tracking under extreme sensory occlusion.

Degree: MS, Artificial Intelligence, 2014, University of Georgia

 Robot localization under extreme occlusion is a common scenario in the real world. Examples include an autonomous car following another car along long stretches of… (more)

Subjects/Keywords: Particle Filter

…time. We further introduce a modification to the traditional Nested Particle Filter that… …typical MCL algorithm, let us look at the Nested MCL algorithm. The Nested Particle Filter or… …NPF” for short, is a Particle Filter modified to not only localize the subject robot (… …that is similar to the one used for localizing roboti . The Nested Particle Filter (NPF… …modified to become recursive for the Nested Particle Filter or ”NPF”. 6 Propagation… 

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APA (6th Edition):

Marathe, K. P. (2014). An Adaptive Nested Particle Filter with Advanced Weighting to handle localization and tracking under extreme sensory occlusion. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/marathe_kedar_p_201412_ms

Chicago Manual of Style (16th Edition):

Marathe, Kedar Pramodan. “An Adaptive Nested Particle Filter with Advanced Weighting to handle localization and tracking under extreme sensory occlusion.” 2014. Masters Thesis, University of Georgia. Accessed March 24, 2019. http://purl.galileo.usg.edu/uga_etd/marathe_kedar_p_201412_ms.

MLA Handbook (7th Edition):

Marathe, Kedar Pramodan. “An Adaptive Nested Particle Filter with Advanced Weighting to handle localization and tracking under extreme sensory occlusion.” 2014. Web. 24 Mar 2019.

Vancouver:

Marathe KP. An Adaptive Nested Particle Filter with Advanced Weighting to handle localization and tracking under extreme sensory occlusion. [Internet] [Masters thesis]. University of Georgia; 2014. [cited 2019 Mar 24]. Available from: http://purl.galileo.usg.edu/uga_etd/marathe_kedar_p_201412_ms.

Council of Science Editors:

Marathe KP. An Adaptive Nested Particle Filter with Advanced Weighting to handle localization and tracking under extreme sensory occlusion. [Masters Thesis]. University of Georgia; 2014. Available from: http://purl.galileo.usg.edu/uga_etd/marathe_kedar_p_201412_ms


University of Alberta

6. Shenoy, Arjun Vsiwanath. Unconstrained nonlinear state estimation for chemical processes.

Degree: MS, Department of Chemical and Materials Engineering, 2010, University of Alberta

 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… (more)

Subjects/Keywords: Kalman filter; Particle filter; Estimation theory; polymer reactors

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APA (6th Edition):

Shenoy, A. V. (2010). Unconstrained nonlinear state estimation for chemical processes. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/n009w369x

Chicago Manual of Style (16th Edition):

Shenoy, Arjun Vsiwanath. “Unconstrained nonlinear state estimation for chemical processes.” 2010. Masters Thesis, University of Alberta. Accessed March 24, 2019. https://era.library.ualberta.ca/files/n009w369x.

MLA Handbook (7th Edition):

Shenoy, Arjun Vsiwanath. “Unconstrained nonlinear state estimation for chemical processes.” 2010. Web. 24 Mar 2019.

Vancouver:

Shenoy AV. Unconstrained nonlinear state estimation for chemical processes. [Internet] [Masters thesis]. University of Alberta; 2010. [cited 2019 Mar 24]. Available from: https://era.library.ualberta.ca/files/n009w369x.

Council of Science Editors:

Shenoy AV. Unconstrained nonlinear state estimation for chemical processes. [Masters Thesis]. University of Alberta; 2010. Available from: https://era.library.ualberta.ca/files/n009w369x


Cal Poly

7. Losie, Philip M. Detection and Tracking of Stealthy Targets Using Particle Filters.

Degree: MS, Electrical Engineering, 2009, Cal Poly

 In recent years, the particle filter has gained prominence in the area of target tracking because it is robust to non-linear target motion and non-Gaussian… (more)

Subjects/Keywords: particle filter; target tracking; track-before-detect; Kalman filter; Signal Processing

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APA (6th Edition):

Losie, P. M. (2009). Detection and Tracking of Stealthy Targets Using Particle Filters. (Masters Thesis). Cal Poly. Retrieved from http://digitalcommons.calpoly.edu/theses/227 ; 10.15368/theses.2009.194

Chicago Manual of Style (16th Edition):

Losie, Philip M. “Detection and Tracking of Stealthy Targets Using Particle Filters.” 2009. Masters Thesis, Cal Poly. Accessed March 24, 2019. http://digitalcommons.calpoly.edu/theses/227 ; 10.15368/theses.2009.194.

MLA Handbook (7th Edition):

Losie, Philip M. “Detection and Tracking of Stealthy Targets Using Particle Filters.” 2009. Web. 24 Mar 2019.

Vancouver:

Losie PM. Detection and Tracking of Stealthy Targets Using Particle Filters. [Internet] [Masters thesis]. Cal Poly; 2009. [cited 2019 Mar 24]. Available from: http://digitalcommons.calpoly.edu/theses/227 ; 10.15368/theses.2009.194.

Council of Science Editors:

Losie PM. Detection and Tracking of Stealthy Targets Using Particle Filters. [Masters Thesis]. Cal Poly; 2009. Available from: http://digitalcommons.calpoly.edu/theses/227 ; 10.15368/theses.2009.194


Virginia Commonwealth University

8. Conte, Armond S, II. Censoring and Fusion in Non-linear Distributed Tracking Systems with Application to 2D Radar.

Degree: MS, Engineering, 2015, Virginia Commonwealth University

  The objective of this research is to study various methods for censoring state estimate updates generated from radar measurements. The generated 2-D radar data… (more)

Subjects/Keywords: radar; fusion; censoring; tracking; particle filter; kalman filter; Signal Processing

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APA (6th Edition):

Conte, Armond S, I. (2015). Censoring and Fusion in Non-linear Distributed Tracking Systems with Application to 2D Radar. (Thesis). Virginia Commonwealth University. Retrieved from https://scholarscompass.vcu.edu/etd/4068

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Conte, Armond S, II. “Censoring and Fusion in Non-linear Distributed Tracking Systems with Application to 2D Radar.” 2015. Thesis, Virginia Commonwealth University. Accessed March 24, 2019. https://scholarscompass.vcu.edu/etd/4068.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Conte, Armond S, II. “Censoring and Fusion in Non-linear Distributed Tracking Systems with Application to 2D Radar.” 2015. Web. 24 Mar 2019.

Vancouver:

Conte, Armond S I. Censoring and Fusion in Non-linear Distributed Tracking Systems with Application to 2D Radar. [Internet] [Thesis]. Virginia Commonwealth University; 2015. [cited 2019 Mar 24]. Available from: https://scholarscompass.vcu.edu/etd/4068.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Conte, Armond S I. Censoring and Fusion in Non-linear Distributed Tracking Systems with Application to 2D Radar. [Thesis]. Virginia Commonwealth University; 2015. Available from: https://scholarscompass.vcu.edu/etd/4068

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Tennessee – Knoxville

9. Collins, John Parnell. Comparison of Methods for Estimating Stochastic Volatility.

Degree: MS, Mathematics, 2013, University of Tennessee – Knoxville

  Understanding the ever changing stock market has long been of interest to both academic and financial institutions. The early attempts to model the dynamics… (more)

Subjects/Keywords: Particle Filter; Gibbs Sampling; Kalman Filter; Other Applied Mathematics

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APA (6th Edition):

Collins, J. P. (2013). Comparison of Methods for Estimating Stochastic Volatility. (Thesis). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_gradthes/2403

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Collins, John Parnell. “Comparison of Methods for Estimating Stochastic Volatility.” 2013. Thesis, University of Tennessee – Knoxville. Accessed March 24, 2019. https://trace.tennessee.edu/utk_gradthes/2403.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Collins, John Parnell. “Comparison of Methods for Estimating Stochastic Volatility.” 2013. Web. 24 Mar 2019.

Vancouver:

Collins JP. Comparison of Methods for Estimating Stochastic Volatility. [Internet] [Thesis]. University of Tennessee – Knoxville; 2013. [cited 2019 Mar 24]. Available from: https://trace.tennessee.edu/utk_gradthes/2403.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Collins JP. Comparison of Methods for Estimating Stochastic Volatility. [Thesis]. University of Tennessee – Knoxville; 2013. Available from: https://trace.tennessee.edu/utk_gradthes/2403

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Urbana-Champaign

10. Medarametla, Krishna Kalyan. Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter.

Degree: MS, 0133, 2014, University of Illinois – Urbana-Champaign

 In a recent work it has been shown that importance sampling can be avoided in particle filter through an innovation structure inspired by traditional nonlinear… (more)

Subjects/Keywords: Extended Kalman filter; Feedback particle filter; Comparison; Nonlinear filtering

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APA (6th Edition):

Medarametla, K. K. (2014). Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/50584

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Medarametla, Krishna Kalyan. “Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter.” 2014. Thesis, University of Illinois – Urbana-Champaign. Accessed March 24, 2019. http://hdl.handle.net/2142/50584.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Medarametla, Krishna Kalyan. “Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter.” 2014. Web. 24 Mar 2019.

Vancouver:

Medarametla KK. Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2014. [cited 2019 Mar 24]. Available from: http://hdl.handle.net/2142/50584.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Medarametla KK. Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter. [Thesis]. University of Illinois – Urbana-Champaign; 2014. Available from: http://hdl.handle.net/2142/50584

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Urbana-Champaign

11. Baillio, Brad A. Multirobot Tethering for Localization and Control.

Degree: MS, Electrical and Computer Engineering, 2009, University of Illinois – Urbana-Champaign

Particle filtering has proven to be an effective localization method for wheeled autonomous vehicles. For a given map, a sensor model, and observations, occasions arise… (more)

Subjects/Keywords: Particle filter; Tethering; Robotics; H infinity Control; Embedded; Linux; Bayes Filter; Laser Rangefinder (Lidar)

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APA (6th Edition):

Baillio, B. A. (2009). Multirobot Tethering for Localization and Control. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/11975

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Baillio, Brad A. “Multirobot Tethering for Localization and Control.” 2009. Thesis, University of Illinois – Urbana-Champaign. Accessed March 24, 2019. http://hdl.handle.net/2142/11975.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Baillio, Brad A. “Multirobot Tethering for Localization and Control.” 2009. Web. 24 Mar 2019.

Vancouver:

Baillio BA. Multirobot Tethering for Localization and Control. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2009. [cited 2019 Mar 24]. Available from: http://hdl.handle.net/2142/11975.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Baillio BA. Multirobot Tethering for Localization and Control. [Thesis]. University of Illinois – Urbana-Champaign; 2009. Available from: http://hdl.handle.net/2142/11975

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Brigham Young University

12. Huber, Braden Russell. Radio Determination on Mini-UAV Platforms: Tracking and Locating Radio Transmitters.

Degree: MS, 2009, Brigham Young University

  Aircraft in the US are equipped with Emergency Locator Transmitters (ELTs). In emergency situations these beacons are activated, providing a radio signal that can… (more)

Subjects/Keywords: radiolocation; radio direction finding; particle filter; unscented Kalman filter; state estimation; Computer Sciences

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APA (6th Edition):

Huber, B. R. (2009). Radio Determination on Mini-UAV Platforms: Tracking and Locating Radio Transmitters. (Masters Thesis). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=2742&context=etd

Chicago Manual of Style (16th Edition):

Huber, Braden Russell. “Radio Determination on Mini-UAV Platforms: Tracking and Locating Radio Transmitters.” 2009. Masters Thesis, Brigham Young University. Accessed March 24, 2019. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=2742&context=etd.

MLA Handbook (7th Edition):

Huber, Braden Russell. “Radio Determination on Mini-UAV Platforms: Tracking and Locating Radio Transmitters.” 2009. Web. 24 Mar 2019.

Vancouver:

Huber BR. Radio Determination on Mini-UAV Platforms: Tracking and Locating Radio Transmitters. [Internet] [Masters thesis]. Brigham Young University; 2009. [cited 2019 Mar 24]. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=2742&context=etd.

Council of Science Editors:

Huber BR. Radio Determination on Mini-UAV Platforms: Tracking and Locating Radio Transmitters. [Masters Thesis]. Brigham Young University; 2009. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=2742&context=etd


Brigham Young University

13. Cannon, Brandon Jeffrey. Fault Detection for Unmanned Aerial Vehicles with Non-Redundant Sensors.

Degree: MS, 2014, Brigham Young University

 To operate, autonomous systems of necessity employ a variety of sensors to perceive their environment. Many small unmanned aerial vehicles (UAV) are unable to carry… (more)

Subjects/Keywords: fault-detection; Kalman filter; particle filter; non-redundant sensor; estimator; UAV; unmanned aircraft; Mechanical Engineering

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APA (6th Edition):

Cannon, B. J. (2014). Fault Detection for Unmanned Aerial Vehicles with Non-Redundant Sensors. (Masters Thesis). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=6307&context=etd

Chicago Manual of Style (16th Edition):

Cannon, Brandon Jeffrey. “Fault Detection for Unmanned Aerial Vehicles with Non-Redundant Sensors.” 2014. Masters Thesis, Brigham Young University. Accessed March 24, 2019. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=6307&context=etd.

MLA Handbook (7th Edition):

Cannon, Brandon Jeffrey. “Fault Detection for Unmanned Aerial Vehicles with Non-Redundant Sensors.” 2014. Web. 24 Mar 2019.

Vancouver:

Cannon BJ. Fault Detection for Unmanned Aerial Vehicles with Non-Redundant Sensors. [Internet] [Masters thesis]. Brigham Young University; 2014. [cited 2019 Mar 24]. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=6307&context=etd.

Council of Science Editors:

Cannon BJ. Fault Detection for Unmanned Aerial Vehicles with Non-Redundant Sensors. [Masters Thesis]. Brigham Young University; 2014. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=6307&context=etd


University of South Carolina

14. Walker, Eric Alan. Comparison of a Particle Filter and Other State Estimation Methods for Prognostics of Lithium-Ion Batteries.

Degree: MS, Chemical Engineering, 2013, University of South Carolina

  A particle filter (PF) is shown to be more accurate than non-linear least squares (NLLS) and an unscented Kalman filter (UKF) for predicting the… (more)

Subjects/Keywords: Chemical Engineering; Engineering; Equivalent circuit model; Lithium-ion battery; Particle filter; Remaining useful life; Single particle model; Unscented Kalman filter

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APA (6th Edition):

Walker, E. A. (2013). Comparison of a Particle Filter and Other State Estimation Methods for Prognostics of Lithium-Ion Batteries. (Masters Thesis). University of South Carolina. Retrieved from https://scholarcommons.sc.edu/etd/2565

Chicago Manual of Style (16th Edition):

Walker, Eric Alan. “Comparison of a Particle Filter and Other State Estimation Methods for Prognostics of Lithium-Ion Batteries.” 2013. Masters Thesis, University of South Carolina. Accessed March 24, 2019. https://scholarcommons.sc.edu/etd/2565.

MLA Handbook (7th Edition):

Walker, Eric Alan. “Comparison of a Particle Filter and Other State Estimation Methods for Prognostics of Lithium-Ion Batteries.” 2013. Web. 24 Mar 2019.

Vancouver:

Walker EA. Comparison of a Particle Filter and Other State Estimation Methods for Prognostics of Lithium-Ion Batteries. [Internet] [Masters thesis]. University of South Carolina; 2013. [cited 2019 Mar 24]. Available from: https://scholarcommons.sc.edu/etd/2565.

Council of Science Editors:

Walker EA. Comparison of a Particle Filter and Other State Estimation Methods for Prognostics of Lithium-Ion Batteries. [Masters Thesis]. University of South Carolina; 2013. Available from: https://scholarcommons.sc.edu/etd/2565


University of Alberta

15. Hladky, Stephen Michael. Predicting opponent locations in first-person shooter video games.

Degree: MS, Department of Computing Science, 2009, University of Alberta

 Commercial video game developers constantly strive to create intelligent humanoid characters that are controlled by computers. To ensure computer opponents are challenging to human players,… (more)

Subjects/Keywords: opponent modelling; particle filter; hidden semi-Markov model; believability; video games

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APA (6th Edition):

Hladky, S. M. (2009). Predicting opponent locations in first-person shooter video games. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/5x21tg037

Chicago Manual of Style (16th Edition):

Hladky, Stephen Michael. “Predicting opponent locations in first-person shooter video games.” 2009. Masters Thesis, University of Alberta. Accessed March 24, 2019. https://era.library.ualberta.ca/files/5x21tg037.

MLA Handbook (7th Edition):

Hladky, Stephen Michael. “Predicting opponent locations in first-person shooter video games.” 2009. Web. 24 Mar 2019.

Vancouver:

Hladky SM. Predicting opponent locations in first-person shooter video games. [Internet] [Masters thesis]. University of Alberta; 2009. [cited 2019 Mar 24]. Available from: https://era.library.ualberta.ca/files/5x21tg037.

Council of Science Editors:

Hladky SM. Predicting opponent locations in first-person shooter video games. [Masters Thesis]. University of Alberta; 2009. Available from: https://era.library.ualberta.ca/files/5x21tg037


Utah State University

16. Rawlings, Dustin. Extracting Atmospheric Profiles from Hyperspectral Data Using Particle Filters.

Degree: MS, Electrical and Computer Engineering, 2013, Utah State University

  Removing the effects of the atmosphere from remote sensing data requires accurate knowledge of the physical properties of the atmosphere during the time of… (more)

Subjects/Keywords: Atmosphere; Hyperspectral; Particle Filter; Electrical and Computer Engineering

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APA (6th Edition):

Rawlings, D. (2013). Extracting Atmospheric Profiles from Hyperspectral Data Using Particle Filters. (Masters Thesis). Utah State University. Retrieved from https://digitalcommons.usu.edu/etd/1533

Chicago Manual of Style (16th Edition):

Rawlings, Dustin. “Extracting Atmospheric Profiles from Hyperspectral Data Using Particle Filters.” 2013. Masters Thesis, Utah State University. Accessed March 24, 2019. https://digitalcommons.usu.edu/etd/1533.

MLA Handbook (7th Edition):

Rawlings, Dustin. “Extracting Atmospheric Profiles from Hyperspectral Data Using Particle Filters.” 2013. Web. 24 Mar 2019.

Vancouver:

Rawlings D. Extracting Atmospheric Profiles from Hyperspectral Data Using Particle Filters. [Internet] [Masters thesis]. Utah State University; 2013. [cited 2019 Mar 24]. Available from: https://digitalcommons.usu.edu/etd/1533.

Council of Science Editors:

Rawlings D. Extracting Atmospheric Profiles from Hyperspectral Data Using Particle Filters. [Masters Thesis]. Utah State University; 2013. Available from: https://digitalcommons.usu.edu/etd/1533


Vanderbilt University

17. Weng, Jiannian. Dynamic Bayesian Network Based Fault Diagnosis on Nonlinear Dynamic Systems.

Degree: MS, Computer Science, 2013, Vanderbilt University

 Fault diagnosis approaches for nonlinear real-world systems play a very important role in maintaining dependable, robust operations of safety-critical systems like aircraft, automobiles, power plants… (more)

Subjects/Keywords: Particle Filter; Fault Diagnosis; Dynamic Bayesian Network; Nonlinear

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APA (6th Edition):

Weng, J. (2013). Dynamic Bayesian Network Based Fault Diagnosis on Nonlinear Dynamic Systems. (Masters Thesis). Vanderbilt University. Retrieved from http://etd.library.vanderbilt.edu/available/etd-04012013-232835/ ;

Chicago Manual of Style (16th Edition):

Weng, Jiannian. “Dynamic Bayesian Network Based Fault Diagnosis on Nonlinear Dynamic Systems.” 2013. Masters Thesis, Vanderbilt University. Accessed March 24, 2019. http://etd.library.vanderbilt.edu/available/etd-04012013-232835/ ;.

MLA Handbook (7th Edition):

Weng, Jiannian. “Dynamic Bayesian Network Based Fault Diagnosis on Nonlinear Dynamic Systems.” 2013. Web. 24 Mar 2019.

Vancouver:

Weng J. Dynamic Bayesian Network Based Fault Diagnosis on Nonlinear Dynamic Systems. [Internet] [Masters thesis]. Vanderbilt University; 2013. [cited 2019 Mar 24]. Available from: http://etd.library.vanderbilt.edu/available/etd-04012013-232835/ ;.

Council of Science Editors:

Weng J. Dynamic Bayesian Network Based Fault Diagnosis on Nonlinear Dynamic Systems. [Masters Thesis]. Vanderbilt University; 2013. Available from: http://etd.library.vanderbilt.edu/available/etd-04012013-232835/ ;


Rochester Institute of Technology

18. Lauzon, Jacob F. Sensor Fusion and Deep Learning for Indoor Agent Localization.

Degree: MS, Computer Engineering, 2017, Rochester Institute of Technology

  Autonomous, self-navigating agents have been rising in popularity due to a push for a more technologically aided future. From cars to vacuum cleaners, the… (more)

Subjects/Keywords: Autonomous; Deep learning; Localization; Omni-vision; Particle filter; Wheelchair

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APA (6th Edition):

Lauzon, J. F. (2017). Sensor Fusion and Deep Learning for Indoor Agent Localization. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9519

Chicago Manual of Style (16th Edition):

Lauzon, Jacob F. “Sensor Fusion and Deep Learning for Indoor Agent Localization.” 2017. Masters Thesis, Rochester Institute of Technology. Accessed March 24, 2019. https://scholarworks.rit.edu/theses/9519.

MLA Handbook (7th Edition):

Lauzon, Jacob F. “Sensor Fusion and Deep Learning for Indoor Agent Localization.” 2017. Web. 24 Mar 2019.

Vancouver:

Lauzon JF. Sensor Fusion and Deep Learning for Indoor Agent Localization. [Internet] [Masters thesis]. Rochester Institute of Technology; 2017. [cited 2019 Mar 24]. Available from: https://scholarworks.rit.edu/theses/9519.

Council of Science Editors:

Lauzon JF. Sensor Fusion and Deep Learning for Indoor Agent Localization. [Masters Thesis]. Rochester Institute of Technology; 2017. Available from: https://scholarworks.rit.edu/theses/9519


Virginia Tech

19. Chambers, Micah Christopher. Full Brain Blood-Oxygen-Level-Dependent Signal Parameter Estimation Using Particle Filters.

Degree: MS, Electrical and Computer Engineering, 2010, Virginia Tech

 Traditional methods of analyzing functional Magnetic Resonance Images use a linear combination of just a few static regressors. This work demonstrates an alternative approach using… (more)

Subjects/Keywords: BOLD Response; FMRI; Nonlinear Systems; Particle Filter; Bayesian Statistics; System Identification

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APA (6th Edition):

Chambers, M. C. (2010). Full Brain Blood-Oxygen-Level-Dependent Signal Parameter Estimation Using Particle Filters. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/35143

Chicago Manual of Style (16th Edition):

Chambers, Micah Christopher. “Full Brain Blood-Oxygen-Level-Dependent Signal Parameter Estimation Using Particle Filters.” 2010. Masters Thesis, Virginia Tech. Accessed March 24, 2019. http://hdl.handle.net/10919/35143.

MLA Handbook (7th Edition):

Chambers, Micah Christopher. “Full Brain Blood-Oxygen-Level-Dependent Signal Parameter Estimation Using Particle Filters.” 2010. Web. 24 Mar 2019.

Vancouver:

Chambers MC. Full Brain Blood-Oxygen-Level-Dependent Signal Parameter Estimation Using Particle Filters. [Internet] [Masters thesis]. Virginia Tech; 2010. [cited 2019 Mar 24]. Available from: http://hdl.handle.net/10919/35143.

Council of Science Editors:

Chambers MC. Full Brain Blood-Oxygen-Level-Dependent Signal Parameter Estimation Using Particle Filters. [Masters Thesis]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/35143


Virginia Tech

20. Mundle, Aditya Ramesh. Blood-Oxygen-Level-Dependent Parameter Identification using Multimodal Neuroimaging and Particle Filters.

Degree: MS, Electrical and Computer Engineering, 2012, Virginia Tech

 The Blood Oxygen Level Dependent (BOLD) signal provides indirect estimates of neural activity. The parameters of this BOLD signal can give information about the pathophysiological… (more)

Subjects/Keywords: BOLD Response; Nonlinear Systems; Overparameterization; System Identification; Particle Filter; Multimodal Neuroimaging

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APA (6th Edition):

Mundle, A. R. (2012). Blood-Oxygen-Level-Dependent Parameter Identification using Multimodal Neuroimaging and Particle Filters. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/31092

Chicago Manual of Style (16th Edition):

Mundle, Aditya Ramesh. “Blood-Oxygen-Level-Dependent Parameter Identification using Multimodal Neuroimaging and Particle Filters.” 2012. Masters Thesis, Virginia Tech. Accessed March 24, 2019. http://hdl.handle.net/10919/31092.

MLA Handbook (7th Edition):

Mundle, Aditya Ramesh. “Blood-Oxygen-Level-Dependent Parameter Identification using Multimodal Neuroimaging and Particle Filters.” 2012. Web. 24 Mar 2019.

Vancouver:

Mundle AR. Blood-Oxygen-Level-Dependent Parameter Identification using Multimodal Neuroimaging and Particle Filters. [Internet] [Masters thesis]. Virginia Tech; 2012. [cited 2019 Mar 24]. Available from: http://hdl.handle.net/10919/31092.

Council of Science Editors:

Mundle AR. Blood-Oxygen-Level-Dependent Parameter Identification using Multimodal Neuroimaging and Particle Filters. [Masters Thesis]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/31092


University of Virginia

21. Qureshi, Muhammad. Receiver-Based Algorithm for Bidirectional Nonlinear Satcom Channels.

Degree: MS, Electrical Engineering, 2014, University of Virginia

 Bidirectional satellite communication between earth terminals on the same frequency at the same time is an emerging means of doubling spectral efficiency on satellite channels.… (more)

Subjects/Keywords: Nonlinear channel; particle filter; bootstrap filter; MAP; inverter; saleh model; bayesian estimation; satellite communications; adaptive canceller; 16-APSK

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APA (6th Edition):

Qureshi, M. (2014). Receiver-Based Algorithm for Bidirectional Nonlinear Satcom Channels. (Doctoral Dissertation). University of Virginia. Retrieved from http://libra.virginia.edu/catalog/libra-oa:7248

Chicago Manual of Style (16th Edition):

Qureshi, Muhammad. “Receiver-Based Algorithm for Bidirectional Nonlinear Satcom Channels.” 2014. Doctoral Dissertation, University of Virginia. Accessed March 24, 2019. http://libra.virginia.edu/catalog/libra-oa:7248.

MLA Handbook (7th Edition):

Qureshi, Muhammad. “Receiver-Based Algorithm for Bidirectional Nonlinear Satcom Channels.” 2014. Web. 24 Mar 2019.

Vancouver:

Qureshi M. Receiver-Based Algorithm for Bidirectional Nonlinear Satcom Channels. [Internet] [Doctoral dissertation]. University of Virginia; 2014. [cited 2019 Mar 24]. Available from: http://libra.virginia.edu/catalog/libra-oa:7248.

Council of Science Editors:

Qureshi M. Receiver-Based Algorithm for Bidirectional Nonlinear Satcom Channels. [Doctoral Dissertation]. University of Virginia; 2014. Available from: http://libra.virginia.edu/catalog/libra-oa:7248


University of Florida

22. Yoon, Jae Myung. A Comparative Study of Adaptive MCMC Based Particle Filtering Methods.

Degree: MS, Mechanical Engineering - Mechanical and Aerospace Engineering, 2012, University of Florida

 In this thesis, we present a comparative study of conventional particle filtering (PF) algorithms for tracking applications. Through the review from the generic PF to… (more)

Subjects/Keywords: Approximation; Covariance; Graphics; Kalman filters; Noise measurement; Particle density; Quantum statistics; Standard deviation; State estimation; Trajectories; filter  – filtering  – mcmc  – particle  – tracking

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APA (6th Edition):

Yoon, J. M. (2012). A Comparative Study of Adaptive MCMC Based Particle Filtering Methods. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044219

Chicago Manual of Style (16th Edition):

Yoon, Jae Myung. “A Comparative Study of Adaptive MCMC Based Particle Filtering Methods.” 2012. Masters Thesis, University of Florida. Accessed March 24, 2019. http://ufdc.ufl.edu/UFE0044219.

MLA Handbook (7th Edition):

Yoon, Jae Myung. “A Comparative Study of Adaptive MCMC Based Particle Filtering Methods.” 2012. Web. 24 Mar 2019.

Vancouver:

Yoon JM. A Comparative Study of Adaptive MCMC Based Particle Filtering Methods. [Internet] [Masters thesis]. University of Florida; 2012. [cited 2019 Mar 24]. Available from: http://ufdc.ufl.edu/UFE0044219.

Council of Science Editors:

Yoon JM. A Comparative Study of Adaptive MCMC Based Particle Filtering Methods. [Masters Thesis]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044219

23. Ghiotto, Shane. Comparison of nonlinear filtering techniques.

Degree: MS, 0133, 2014, University of Illinois – Urbana-Champaign

 In a recent work it is shown that importance sampling can be avoided in the particle filter through an innovation structure inspired by traditional nonlinear… (more)

Subjects/Keywords: Filtering; state estimation; particle filtering; Kalman filter; feedback particle filter

…the Kalman algorithm [9]. Another common approach is to use a particle filter… …Various resampling techniques are available to deal with the traditional particle filter issues… …approaches, such as the feedback particle filter (FPF) in [16, 14], seek to… …with the feedback particle filter. The remainder of the thesis is organized as follows… …chapter 2 provides background on the extended Kalman filter and feedback particle filter… 

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APA (6th Edition):

Ghiotto, S. (2014). Comparison of nonlinear filtering techniques. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/49437

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ghiotto, Shane. “Comparison of nonlinear filtering techniques.” 2014. Thesis, University of Illinois – Urbana-Champaign. Accessed March 24, 2019. http://hdl.handle.net/2142/49437.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ghiotto, Shane. “Comparison of nonlinear filtering techniques.” 2014. Web. 24 Mar 2019.

Vancouver:

Ghiotto S. Comparison of nonlinear filtering techniques. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2014. [cited 2019 Mar 24]. Available from: http://hdl.handle.net/2142/49437.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ghiotto S. Comparison of nonlinear filtering techniques. [Thesis]. University of Illinois – Urbana-Champaign; 2014. Available from: http://hdl.handle.net/2142/49437

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Minnesota

24. Collins, Aaron Michael. Ultrafine particle loss in aerosol diluters.

Degree: MS, Mechanical Engineering, 2010, University of Minnesota

University of Minnesota M.S. thesis. December 2010. Major: Mechanical Engineering. Advisor: David B. Kittelson. 1 computer file (PDF); viii, 117 pages, appendices I-II. Ill. (some… (more)

Subjects/Keywords: Aerosol diluter; Particle loss; Diffusion driven; TSI 3302, MSP 1100, a “leaky filter”; Mechanical engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Collins, A. M. (2010). Ultrafine particle loss in aerosol diluters. (Masters Thesis). University of Minnesota. Retrieved from http://purl.umn.edu/103245

Chicago Manual of Style (16th Edition):

Collins, Aaron Michael. “Ultrafine particle loss in aerosol diluters.” 2010. Masters Thesis, University of Minnesota. Accessed March 24, 2019. http://purl.umn.edu/103245.

MLA Handbook (7th Edition):

Collins, Aaron Michael. “Ultrafine particle loss in aerosol diluters.” 2010. Web. 24 Mar 2019.

Vancouver:

Collins AM. Ultrafine particle loss in aerosol diluters. [Internet] [Masters thesis]. University of Minnesota; 2010. [cited 2019 Mar 24]. Available from: http://purl.umn.edu/103245.

Council of Science Editors:

Collins AM. Ultrafine particle loss in aerosol diluters. [Masters Thesis]. University of Minnesota; 2010. Available from: http://purl.umn.edu/103245


Penn State University

25. Fox, Evan M. Fluid Dynamic Study of a Compliant Model for an Inferior Vena Cava Filter.

Degree: MS, Bioengineering, 2013, Penn State University

 Deep vein thrombosis afflicts a reported 1 in 1000 persons, resulting in severe medical consequences for many as the thrombus may dislodge to form a… (more)

Subjects/Keywords: deep vein thrombosis; pulmonary embolism; inferior vena cava filter; particle image velocimetry

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APA (6th Edition):

Fox, E. M. (2013). Fluid Dynamic Study of a Compliant Model for an Inferior Vena Cava Filter. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/18070

Chicago Manual of Style (16th Edition):

Fox, Evan M. “Fluid Dynamic Study of a Compliant Model for an Inferior Vena Cava Filter.” 2013. Masters Thesis, Penn State University. Accessed March 24, 2019. https://etda.libraries.psu.edu/catalog/18070.

MLA Handbook (7th Edition):

Fox, Evan M. “Fluid Dynamic Study of a Compliant Model for an Inferior Vena Cava Filter.” 2013. Web. 24 Mar 2019.

Vancouver:

Fox EM. Fluid Dynamic Study of a Compliant Model for an Inferior Vena Cava Filter. [Internet] [Masters thesis]. Penn State University; 2013. [cited 2019 Mar 24]. Available from: https://etda.libraries.psu.edu/catalog/18070.

Council of Science Editors:

Fox EM. Fluid Dynamic Study of a Compliant Model for an Inferior Vena Cava Filter. [Masters Thesis]. Penn State University; 2013. Available from: https://etda.libraries.psu.edu/catalog/18070

26. Nouri, Cameron Ramin. INDOOR LOCATION TRACKING AND ORIENTATION ESTIMATION USING A PARTICLE FILTER, INS, AND RSSI.

Degree: MS, Electrical Engineering, 2015, Cal Poly

  With the advent of wireless sensor technologies becoming more and more common-place in wearable devices and smartphones, indoor localization is becoming a heavily researched… (more)

Subjects/Keywords: Localization; RSSI; IMU; Particle Filter

…42 Figure 25: Sensor Fusion - Particle Filter - INS and RSSI combined, Y-axis movement, 100… …44 Figure 26: Sensor Fusion - Particle Filter - INS and RSSI combined, Stationary, 500… …45 Page viii Figure 27: Sensor Fusion - Particle Filter - INS and RSSI combined, Y-axis… …46 Figure 28: Sensor Fusion - Particle Filter - INS and RSSI combined, X-axis movement… …and the Particle Filter with current tracking techniques generally using an Extended Kalman… 

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APA (6th Edition):

Nouri, C. R. (2015). INDOOR LOCATION TRACKING AND ORIENTATION ESTIMATION USING A PARTICLE FILTER, INS, AND RSSI. (Masters Thesis). Cal Poly. Retrieved from http://digitalcommons.calpoly.edu/theses/1356 ; 10.15368/theses.2015.1

Chicago Manual of Style (16th Edition):

Nouri, Cameron Ramin. “INDOOR LOCATION TRACKING AND ORIENTATION ESTIMATION USING A PARTICLE FILTER, INS, AND RSSI.” 2015. Masters Thesis, Cal Poly. Accessed March 24, 2019. http://digitalcommons.calpoly.edu/theses/1356 ; 10.15368/theses.2015.1.

MLA Handbook (7th Edition):

Nouri, Cameron Ramin. “INDOOR LOCATION TRACKING AND ORIENTATION ESTIMATION USING A PARTICLE FILTER, INS, AND RSSI.” 2015. Web. 24 Mar 2019.

Vancouver:

Nouri CR. INDOOR LOCATION TRACKING AND ORIENTATION ESTIMATION USING A PARTICLE FILTER, INS, AND RSSI. [Internet] [Masters thesis]. Cal Poly; 2015. [cited 2019 Mar 24]. Available from: http://digitalcommons.calpoly.edu/theses/1356 ; 10.15368/theses.2015.1.

Council of Science Editors:

Nouri CR. INDOOR LOCATION TRACKING AND ORIENTATION ESTIMATION USING A PARTICLE FILTER, INS, AND RSSI. [Masters Thesis]. Cal Poly; 2015. Available from: http://digitalcommons.calpoly.edu/theses/1356 ; 10.15368/theses.2015.1


Arizona State University

27. Liu, Shubo. Integrated Waveform-Agile Multi-Modal Track-before-Detect Algorithms for Tracking Low Observable Targets.

Degree: MS, Electrical Engineering, 2012, Arizona State University

 In this thesis, an integrated waveform-agile multi-modal tracking-beforedetect sensing system is investigated and the performance is evaluated using an experimental platform. The sensing system of… (more)

Subjects/Keywords: Electrical engineering; Embedded exponential families; Particle Filter; Track-before-detect; Waveform-agile

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APA (6th Edition):

Liu, S. (2012). Integrated Waveform-Agile Multi-Modal Track-before-Detect Algorithms for Tracking Low Observable Targets. (Masters Thesis). Arizona State University. Retrieved from http://repository.asu.edu/items/14953

Chicago Manual of Style (16th Edition):

Liu, Shubo. “Integrated Waveform-Agile Multi-Modal Track-before-Detect Algorithms for Tracking Low Observable Targets.” 2012. Masters Thesis, Arizona State University. Accessed March 24, 2019. http://repository.asu.edu/items/14953.

MLA Handbook (7th Edition):

Liu, Shubo. “Integrated Waveform-Agile Multi-Modal Track-before-Detect Algorithms for Tracking Low Observable Targets.” 2012. Web. 24 Mar 2019.

Vancouver:

Liu S. Integrated Waveform-Agile Multi-Modal Track-before-Detect Algorithms for Tracking Low Observable Targets. [Internet] [Masters thesis]. Arizona State University; 2012. [cited 2019 Mar 24]. Available from: http://repository.asu.edu/items/14953.

Council of Science Editors:

Liu S. Integrated Waveform-Agile Multi-Modal Track-before-Detect Algorithms for Tracking Low Observable Targets. [Masters Thesis]. Arizona State University; 2012. Available from: http://repository.asu.edu/items/14953


University of Minnesota

28. Collins, Aaron Michael. Ultrafine particle loss in aerosol diluters.

Degree: MS, Mechanical Engineering, 2010, University of Minnesota

 Measurements of high concentration aerosols typically require some method to reduce the concentration of the aerosol to a measureable method. One common method is to… (more)

Subjects/Keywords: Aerosol diluter; Particle loss; Diffusion driven; TSI 3302, MSP 1100, a “leaky filter”; Mechanical engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Collins, A. M. (2010). Ultrafine particle loss in aerosol diluters. (Masters Thesis). University of Minnesota. Retrieved from http://purl.umn.edu/103245

Chicago Manual of Style (16th Edition):

Collins, Aaron Michael. “Ultrafine particle loss in aerosol diluters.” 2010. Masters Thesis, University of Minnesota. Accessed March 24, 2019. http://purl.umn.edu/103245.

MLA Handbook (7th Edition):

Collins, Aaron Michael. “Ultrafine particle loss in aerosol diluters.” 2010. Web. 24 Mar 2019.

Vancouver:

Collins AM. Ultrafine particle loss in aerosol diluters. [Internet] [Masters thesis]. University of Minnesota; 2010. [cited 2019 Mar 24]. Available from: http://purl.umn.edu/103245.

Council of Science Editors:

Collins AM. Ultrafine particle loss in aerosol diluters. [Masters Thesis]. University of Minnesota; 2010. Available from: http://purl.umn.edu/103245


North Carolina State University

29. Girisan, Vivek. Flow Modeling through an Electro-statically Charged Monolith Filter.

Degree: MS, Mechanical Engineering, 2009, North Carolina State University

 GIRISAN, VIVEK. Flow Modeling through an Electro-statically Charged Nano-Particle Filter. (Under the direction of Dr. Andrey Kuznetsov). The modeling of flow thorough regular sized channels… (more)

Subjects/Keywords: aerosol; filtration; micro-flows; monolith filter; particle tracking; multi-physics; electrostatic; nanoparticle

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APA (6th Edition):

Girisan, V. (2009). Flow Modeling through an Electro-statically Charged Monolith Filter. (Thesis). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/1833

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Girisan, Vivek. “Flow Modeling through an Electro-statically Charged Monolith Filter.” 2009. Thesis, North Carolina State University. Accessed March 24, 2019. http://www.lib.ncsu.edu/resolver/1840.16/1833.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Girisan, Vivek. “Flow Modeling through an Electro-statically Charged Monolith Filter.” 2009. Web. 24 Mar 2019.

Vancouver:

Girisan V. Flow Modeling through an Electro-statically Charged Monolith Filter. [Internet] [Thesis]. North Carolina State University; 2009. [cited 2019 Mar 24]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/1833.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Girisan V. Flow Modeling through an Electro-statically Charged Monolith Filter. [Thesis]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/1833

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

30. Mattes, Richard J. Vehicle Localization With A Downward Facing LIDAR.

Degree: MS, Mechanical Engineering, 2015, Penn State University

 Autonomous, or self-driving vehicles hold much promise for the future of personal transportation. Autonomous vehicles have the potential to remove the human error from driving,… (more)

Subjects/Keywords: localization; particle filter; autonomous vehicles; simulation; LIDAR

…3.12 Longitudinal particle filter tracking error with 500 particles, using σd2 =500cm2… …These include: Adam Dean for developing a MATLAB particle filter tutorial that kicked off my… …particle filter vehicle localization using only road intensity features measured from a downward… …facing LIDAR. 3.1 The Particle Filter The Particle Filter is a recursive Bayesian estimator… …estimator, the particle filter is unique in that it represents a system’s state probability… 

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APA (6th Edition):

Mattes, R. J. (2015). Vehicle Localization With A Downward Facing LIDAR. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/26471

Chicago Manual of Style (16th Edition):

Mattes, Richard J. “Vehicle Localization With A Downward Facing LIDAR.” 2015. Masters Thesis, Penn State University. Accessed March 24, 2019. https://etda.libraries.psu.edu/catalog/26471.

MLA Handbook (7th Edition):

Mattes, Richard J. “Vehicle Localization With A Downward Facing LIDAR.” 2015. Web. 24 Mar 2019.

Vancouver:

Mattes RJ. Vehicle Localization With A Downward Facing LIDAR. [Internet] [Masters thesis]. Penn State University; 2015. [cited 2019 Mar 24]. Available from: https://etda.libraries.psu.edu/catalog/26471.

Council of Science Editors:

Mattes RJ. Vehicle Localization With A Downward Facing LIDAR. [Masters Thesis]. Penn State University; 2015. Available from: https://etda.libraries.psu.edu/catalog/26471

[1] [2]

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