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You searched for subject:(Particle Filter). Showing records 1 – 30 of 347 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 · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

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 September 22, 2020. https://era.library.ualberta.ca/files/bz60cx09v.

MLA Handbook (7th Edition):

Ye, Zi. “A Discrete-time Particle Filter and Central Limit Theorem.” 2013. Web. 22 Sep 2020.

Vancouver:

Ye Z. A Discrete-time Particle Filter and Central Limit Theorem. [Internet] [Masters thesis]. University of Alberta; 2013. [cited 2020 Sep 22]. 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

2. Barac, Daniel. Localization algorithms for indoor UAVs.

Degree: UASTECH - Autonomous Unmanned Aircraft Systems Technologies, 2011, Linköping UniversityLinköping University

  The increased market for navigation, localization and mapping system has encouraged the research to dig deeper into these new and challenging areas. The remarkable… (more)

Subjects/Keywords: UAV; particle filter; Octomap; localization

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APA (6th Edition):

Barac, D. (2011). Localization algorithms for indoor UAVs. (Thesis). Linköping UniversityLinköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-72217

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):

Barac, Daniel. “Localization algorithms for indoor UAVs.” 2011. Thesis, Linköping UniversityLinköping University. Accessed September 22, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-72217.

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

MLA Handbook (7th Edition):

Barac, Daniel. “Localization algorithms for indoor UAVs.” 2011. Web. 22 Sep 2020.

Vancouver:

Barac D. Localization algorithms for indoor UAVs. [Internet] [Thesis]. Linköping UniversityLinköping University; 2011. [cited 2020 Sep 22]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-72217.

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

Council of Science Editors:

Barac D. Localization algorithms for indoor UAVs. [Thesis]. Linköping UniversityLinköping University; 2011. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-72217

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


California State University – Chico

3. Daley, Patrick. A REAL-TIME EFFICIENT PARTICLE FILTER ALGORITHM FOR REALISTIC TARGET TRACKING IN GAMES .

Degree: 2012, California State University – Chico

 The challenge for a computer game agent in a partially observable targettracking environment is to estimate where the target might be before taking the next… (more)

Subjects/Keywords: computer games particle filter algorithm

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APA (6th Edition):

Daley, P. (2012). A REAL-TIME EFFICIENT PARTICLE FILTER ALGORITHM FOR REALISTIC TARGET TRACKING IN GAMES . (Thesis). California State University – Chico. Retrieved from http://hdl.handle.net/10211.4/424

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):

Daley, Patrick. “A REAL-TIME EFFICIENT PARTICLE FILTER ALGORITHM FOR REALISTIC TARGET TRACKING IN GAMES .” 2012. Thesis, California State University – Chico. Accessed September 22, 2020. http://hdl.handle.net/10211.4/424.

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

MLA Handbook (7th Edition):

Daley, Patrick. “A REAL-TIME EFFICIENT PARTICLE FILTER ALGORITHM FOR REALISTIC TARGET TRACKING IN GAMES .” 2012. Web. 22 Sep 2020.

Vancouver:

Daley P. A REAL-TIME EFFICIENT PARTICLE FILTER ALGORITHM FOR REALISTIC TARGET TRACKING IN GAMES . [Internet] [Thesis]. California State University – Chico; 2012. [cited 2020 Sep 22]. Available from: http://hdl.handle.net/10211.4/424.

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

Council of Science Editors:

Daley P. A REAL-TIME EFFICIENT PARTICLE FILTER ALGORITHM FOR REALISTIC TARGET TRACKING IN GAMES . [Thesis]. California State University – Chico; 2012. Available from: http://hdl.handle.net/10211.4/424

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


Delft University of Technology

4. Chitchian, M.M. (author). Adapting Particle Filter Algorithms to the GPU Architecture.

Degree: 2011, Delft University of Technology

The particle filter is a Bayesian estimation technique based on Monte Carlo simulations. The non-parametric nature of particle filters makes them ideal for non-linear non-Gaussian… (more)

Subjects/Keywords: particle filter; bayesian estimation; CUDA; GPGPU; GPU; bayes filter; non-linear estimation; distributed particle filter; real-time estimation; parallel particle filter

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

APA (6th Edition):

Chitchian, M. M. (. (2011). Adapting Particle Filter Algorithms to the GPU Architecture. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:9b11258e-cd9c-494d-bbb7-3b85c700b30f

Chicago Manual of Style (16th Edition):

Chitchian, M M (author). “Adapting Particle Filter Algorithms to the GPU Architecture.” 2011. Masters Thesis, Delft University of Technology. Accessed September 22, 2020. http://resolver.tudelft.nl/uuid:9b11258e-cd9c-494d-bbb7-3b85c700b30f.

MLA Handbook (7th Edition):

Chitchian, M M (author). “Adapting Particle Filter Algorithms to the GPU Architecture.” 2011. Web. 22 Sep 2020.

Vancouver:

Chitchian MM(. Adapting Particle Filter Algorithms to the GPU Architecture. [Internet] [Masters thesis]. Delft University of Technology; 2011. [cited 2020 Sep 22]. Available from: http://resolver.tudelft.nl/uuid:9b11258e-cd9c-494d-bbb7-3b85c700b30f.

Council of Science Editors:

Chitchian MM(. Adapting Particle Filter Algorithms to the GPU Architecture. [Masters Thesis]. Delft University of Technology; 2011. Available from: http://resolver.tudelft.nl/uuid:9b11258e-cd9c-494d-bbb7-3b85c700b30f


University of Alberta

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

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 September 22, 2020. https://era.library.ualberta.ca/files/c6969z0831.

MLA Handbook (7th Edition):

Wang, Xingpu. “Web Based Particle Filters.” 2015. Web. 22 Sep 2020.

Vancouver:

Wang X. Web Based Particle Filters. [Internet] [Masters thesis]. University of Alberta; 2015. [cited 2020 Sep 22]. 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

6. 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 September 22, 2020. 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. 22 Sep 2020.

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 2020 Sep 22]. 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


Texas A&M University

7. Noor, Amina. Modeling Gene Regulatory Networks from Time Series Data using Particle Filtering.

Degree: MS, Electrical Engineering, 2012, Texas A&M University

 This thesis considers the problem of learning the structure of gene regulatory networks using gene expression time series data. A more realistic scenario where the… (more)

Subjects/Keywords: gene network modeling; particle filter; lasso

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APA (6th Edition):

Noor, A. (2012). Modeling Gene Regulatory Networks from Time Series Data using Particle Filtering. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9860

Chicago Manual of Style (16th Edition):

Noor, Amina. “Modeling Gene Regulatory Networks from Time Series Data using Particle Filtering.” 2012. Masters Thesis, Texas A&M University. Accessed September 22, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9860.

MLA Handbook (7th Edition):

Noor, Amina. “Modeling Gene Regulatory Networks from Time Series Data using Particle Filtering.” 2012. Web. 22 Sep 2020.

Vancouver:

Noor A. Modeling Gene Regulatory Networks from Time Series Data using Particle Filtering. [Internet] [Masters thesis]. Texas A&M University; 2012. [cited 2020 Sep 22]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9860.

Council of Science Editors:

Noor A. Modeling Gene Regulatory Networks from Time Series Data using Particle Filtering. [Masters Thesis]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9860


Penn State University

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

Degree: 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

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APA (6th Edition):

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

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):

Mattes, Richard J. “Vehicle Localization With A Downward Facing LIDAR.” 2015. Thesis, Penn State University. Accessed September 22, 2020. https://submit-etda.libraries.psu.edu/catalog/26471.

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

MLA Handbook (7th Edition):

Mattes, Richard J. “Vehicle Localization With A Downward Facing LIDAR.” 2015. Web. 22 Sep 2020.

Vancouver:

Mattes RJ. Vehicle Localization With A Downward Facing LIDAR. [Internet] [Thesis]. Penn State University; 2015. [cited 2020 Sep 22]. Available from: https://submit-etda.libraries.psu.edu/catalog/26471.

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

Council of Science Editors:

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

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


University of New South Wales

9. Chen, Yu. Facial Segmentation Using Boosted Dynamic Mixture Active Shape Model.

Degree: Computer Science & Engineering, 2015, University of New South Wales

 Considerable research has been done on automatic extraction of salient features from human faces in images over the last 20 years. For many existing systems,… (more)

Subjects/Keywords: Particle Filter; Active Shape Model; Machine Learning

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APA (6th Edition):

Chen, Y. (2015). Facial Segmentation Using Boosted Dynamic Mixture Active Shape Model. (Masters Thesis). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/54529 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:35191/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Chen, Yu. “Facial Segmentation Using Boosted Dynamic Mixture Active Shape Model.” 2015. Masters Thesis, University of New South Wales. Accessed September 22, 2020. http://handle.unsw.edu.au/1959.4/54529 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:35191/SOURCE02?view=true.

MLA Handbook (7th Edition):

Chen, Yu. “Facial Segmentation Using Boosted Dynamic Mixture Active Shape Model.” 2015. Web. 22 Sep 2020.

Vancouver:

Chen Y. Facial Segmentation Using Boosted Dynamic Mixture Active Shape Model. [Internet] [Masters thesis]. University of New South Wales; 2015. [cited 2020 Sep 22]. Available from: http://handle.unsw.edu.au/1959.4/54529 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:35191/SOURCE02?view=true.

Council of Science Editors:

Chen Y. Facial Segmentation Using Boosted Dynamic Mixture Active Shape Model. [Masters Thesis]. University of New South Wales; 2015. Available from: http://handle.unsw.edu.au/1959.4/54529 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:35191/SOURCE02?view=true


NSYSU

10. Lin, Yu-Tsen. Improved Particle Filter for Target Tracking in Decentralized Data Fusion System.

Degree: Master, Electrical Engineering, 2009, NSYSU

 In this thesis, we investigate a decentralized data fusion system with improved particle filters for target tracking. In many application areas, it becomes essential to… (more)

Subjects/Keywords: decentralized data fusion; target tracking; particle filter

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APA (6th Edition):

Lin, Y. (2009). Improved Particle Filter for Target Tracking in Decentralized Data Fusion System. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906109-030910

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):

Lin, Yu-Tsen. “Improved Particle Filter for Target Tracking in Decentralized Data Fusion System.” 2009. Thesis, NSYSU. Accessed September 22, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906109-030910.

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

MLA Handbook (7th Edition):

Lin, Yu-Tsen. “Improved Particle Filter for Target Tracking in Decentralized Data Fusion System.” 2009. Web. 22 Sep 2020.

Vancouver:

Lin Y. Improved Particle Filter for Target Tracking in Decentralized Data Fusion System. [Internet] [Thesis]. NSYSU; 2009. [cited 2020 Sep 22]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906109-030910.

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

Council of Science Editors:

Lin Y. Improved Particle Filter for Target Tracking in Decentralized Data Fusion System. [Thesis]. NSYSU; 2009. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0906109-030910

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


University of Texas – Austin

11. Shen, Xiaohu, active 21st century. Bayesian inference methods for next generation DNA sequencing.

Degree: PhD, Electrical and Computer Engineering, 2014, University of Texas – Austin

 Recently developed next-generation sequencing systems are capable of rapid and cost-effective DNA sequencing, thus enabling routine sequencing tasks and taking us one step closer to… (more)

Subjects/Keywords: DNA sequencing; Particle filter; Message passing

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APA (6th Edition):

Shen, Xiaohu, a. 2. c. (2014). Bayesian inference methods for next generation DNA sequencing. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/26176

Chicago Manual of Style (16th Edition):

Shen, Xiaohu, active 21st century. “Bayesian inference methods for next generation DNA sequencing.” 2014. Doctoral Dissertation, University of Texas – Austin. Accessed September 22, 2020. http://hdl.handle.net/2152/26176.

MLA Handbook (7th Edition):

Shen, Xiaohu, active 21st century. “Bayesian inference methods for next generation DNA sequencing.” 2014. Web. 22 Sep 2020.

Vancouver:

Shen, Xiaohu a2c. Bayesian inference methods for next generation DNA sequencing. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2014. [cited 2020 Sep 22]. Available from: http://hdl.handle.net/2152/26176.

Council of Science Editors:

Shen, Xiaohu a2c. Bayesian inference methods for next generation DNA sequencing. [Doctoral Dissertation]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/26176


Delft University of Technology

12. Giannopoulos, Makis (author). Hierarchical Mapping: A Rao-Blackwellized Particle Filter based hierarchical SLAM framework.

Degree: 2017, Delft University of Technology

 Mobile robots need to be fully autonomous in order to perform their tasks inside their environment. To do that, robots need to have an understanding… (more)

Subjects/Keywords: SLAM; mapping; hierarchical mapping; Particle Filter

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APA (6th Edition):

Giannopoulos, M. (. (2017). Hierarchical Mapping: A Rao-Blackwellized Particle Filter based hierarchical SLAM framework. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:2d3532a6-fda2-44ea-b743-b643ad7d122c

Chicago Manual of Style (16th Edition):

Giannopoulos, Makis (author). “Hierarchical Mapping: A Rao-Blackwellized Particle Filter based hierarchical SLAM framework.” 2017. Masters Thesis, Delft University of Technology. Accessed September 22, 2020. http://resolver.tudelft.nl/uuid:2d3532a6-fda2-44ea-b743-b643ad7d122c.

MLA Handbook (7th Edition):

Giannopoulos, Makis (author). “Hierarchical Mapping: A Rao-Blackwellized Particle Filter based hierarchical SLAM framework.” 2017. Web. 22 Sep 2020.

Vancouver:

Giannopoulos M(. Hierarchical Mapping: A Rao-Blackwellized Particle Filter based hierarchical SLAM framework. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Sep 22]. Available from: http://resolver.tudelft.nl/uuid:2d3532a6-fda2-44ea-b743-b643ad7d122c.

Council of Science Editors:

Giannopoulos M(. Hierarchical Mapping: A Rao-Blackwellized Particle Filter based hierarchical SLAM framework. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:2d3532a6-fda2-44ea-b743-b643ad7d122c


Delft University of Technology

13. van Groeningen, Tom (author). Human presence detection using a particle filter on ultrasonic micro-Doppler measurements for assisting rescue work in large buildings.

Degree: 2018, Delft University of Technology

When the re brigade arrives at a burning building, it is of vital importance that people who are still inside can quickly be found. In… (more)

Subjects/Keywords: micro doppler; particle filter; Gaussian approximation

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APA (6th Edition):

van Groeningen, T. (. (2018). Human presence detection using a particle filter on ultrasonic micro-Doppler measurements for assisting rescue work in large buildings. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:467ea25a-e5f3-47e6-857b-3e0510ff52de

Chicago Manual of Style (16th Edition):

van Groeningen, Tom (author). “Human presence detection using a particle filter on ultrasonic micro-Doppler measurements for assisting rescue work in large buildings.” 2018. Masters Thesis, Delft University of Technology. Accessed September 22, 2020. http://resolver.tudelft.nl/uuid:467ea25a-e5f3-47e6-857b-3e0510ff52de.

MLA Handbook (7th Edition):

van Groeningen, Tom (author). “Human presence detection using a particle filter on ultrasonic micro-Doppler measurements for assisting rescue work in large buildings.” 2018. Web. 22 Sep 2020.

Vancouver:

van Groeningen T(. Human presence detection using a particle filter on ultrasonic micro-Doppler measurements for assisting rescue work in large buildings. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Sep 22]. Available from: http://resolver.tudelft.nl/uuid:467ea25a-e5f3-47e6-857b-3e0510ff52de.

Council of Science Editors:

van Groeningen T(. Human presence detection using a particle filter on ultrasonic micro-Doppler measurements for assisting rescue work in large buildings. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:467ea25a-e5f3-47e6-857b-3e0510ff52de


Delft University of Technology

14. Beers, Karlijn (author). Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter.

Degree: 2018, Delft University of Technology

 This thesis explores the usage of the particle filter as a data assimilation technique to estimate subsurface processes, such as reservoir volume change from space-geodetic… (more)

Subjects/Keywords: Data assimilation; Particle Filter; InSAR; Groningen

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APA (6th Edition):

Beers, K. (. (2018). Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:6db5ad75-8b34-4fce-a570-070c7b6bf6b3

Chicago Manual of Style (16th Edition):

Beers, Karlijn (author). “Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter.” 2018. Masters Thesis, Delft University of Technology. Accessed September 22, 2020. http://resolver.tudelft.nl/uuid:6db5ad75-8b34-4fce-a570-070c7b6bf6b3.

MLA Handbook (7th Edition):

Beers, Karlijn (author). “Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter.” 2018. Web. 22 Sep 2020.

Vancouver:

Beers K(. Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Sep 22]. Available from: http://resolver.tudelft.nl/uuid:6db5ad75-8b34-4fce-a570-070c7b6bf6b3.

Council of Science Editors:

Beers K(. Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:6db5ad75-8b34-4fce-a570-070c7b6bf6b3


University of Illinois – Urbana-Champaign

15. Aranguiz, Dario. Low-cost time-of-flight-based localization techniques for robotic applications.

Degree: MS, Electrical & Computer Engr, 2017, University of Illinois – Urbana-Champaign

 This thesis provides an overview of the localization techniques used by the robotic platform Mousr, as well as the modeling assumptions and simulator scaffolding used… (more)

Subjects/Keywords: Robotics; Localization; Particle filter; Time of flight

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

APA (6th Edition):

Aranguiz, D. (2017). Low-cost time-of-flight-based localization techniques for robotic applications. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/99528

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):

Aranguiz, Dario. “Low-cost time-of-flight-based localization techniques for robotic applications.” 2017. Thesis, University of Illinois – Urbana-Champaign. Accessed September 22, 2020. http://hdl.handle.net/2142/99528.

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

MLA Handbook (7th Edition):

Aranguiz, Dario. “Low-cost time-of-flight-based localization techniques for robotic applications.” 2017. Web. 22 Sep 2020.

Vancouver:

Aranguiz D. Low-cost time-of-flight-based localization techniques for robotic applications. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2017. [cited 2020 Sep 22]. Available from: http://hdl.handle.net/2142/99528.

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

Council of Science Editors:

Aranguiz D. Low-cost time-of-flight-based localization techniques for robotic applications. [Thesis]. University of Illinois – Urbana-Champaign; 2017. Available from: http://hdl.handle.net/2142/99528

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


Georgia Tech

16. 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 September 22, 2020. http://hdl.handle.net/1853/56265.

MLA Handbook (7th Edition):

Leonard, Andrew. “Vehicle tracking using ultra-wideband radar.” 2016. Web. 22 Sep 2020.

Vancouver:

Leonard A. Vehicle tracking using ultra-wideband radar. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2020 Sep 22]. 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


Vanderbilt University

17. Patki, Akash. Particle Filter based SLAM to map random environments using “iRobot Roomba”.

Degree: MS, Computer Science, 2011, Vanderbilt University

 For any mobile robot application it is important that a robot knows its location in an operating environment. The map for the operating environment may… (more)

Subjects/Keywords: Particle Filter; Monte Carlo; Mapping; SLAM; Localization

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APA (6th Edition):

Patki, A. (2011). Particle Filter based SLAM to map random environments using “iRobot Roomba”. (Thesis). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/15177

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):

Patki, Akash. “Particle Filter based SLAM to map random environments using “iRobot Roomba”.” 2011. Thesis, Vanderbilt University. Accessed September 22, 2020. http://hdl.handle.net/1803/15177.

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

MLA Handbook (7th Edition):

Patki, Akash. “Particle Filter based SLAM to map random environments using “iRobot Roomba”.” 2011. Web. 22 Sep 2020.

Vancouver:

Patki A. Particle Filter based SLAM to map random environments using “iRobot Roomba”. [Internet] [Thesis]. Vanderbilt University; 2011. [cited 2020 Sep 22]. Available from: http://hdl.handle.net/1803/15177.

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

Council of Science Editors:

Patki A. Particle Filter based SLAM to map random environments using “iRobot Roomba”. [Thesis]. Vanderbilt University; 2011. Available from: http://hdl.handle.net/1803/15177

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


University of Canterbury

18. Gao, Hongzhi. Real Time Human Tracking in Unconstrained Environments.

Degree: PhD, Computer Science, 2011, University of Canterbury

 The tabu search particle filter is proposed in this research based on the integration of the modified tabu search metaheuristic optimization and the genetic particle(more)

Subjects/Keywords: computer vision; real-time tracking; particle filter

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APA (6th Edition):

Gao, H. (2011). Real Time Human Tracking in Unconstrained Environments. (Doctoral Dissertation). University of Canterbury. Retrieved from http://dx.doi.org/10.26021/1741

Chicago Manual of Style (16th Edition):

Gao, Hongzhi. “Real Time Human Tracking in Unconstrained Environments.” 2011. Doctoral Dissertation, University of Canterbury. Accessed September 22, 2020. http://dx.doi.org/10.26021/1741.

MLA Handbook (7th Edition):

Gao, Hongzhi. “Real Time Human Tracking in Unconstrained Environments.” 2011. Web. 22 Sep 2020.

Vancouver:

Gao H. Real Time Human Tracking in Unconstrained Environments. [Internet] [Doctoral dissertation]. University of Canterbury; 2011. [cited 2020 Sep 22]. Available from: http://dx.doi.org/10.26021/1741.

Council of Science Editors:

Gao H. Real Time Human Tracking in Unconstrained Environments. [Doctoral Dissertation]. University of Canterbury; 2011. Available from: http://dx.doi.org/10.26021/1741

19. Särkkä, Simo. Recursive Bayesian Inference on Stochastic Differential Equations.

Degree: 2006, Helsinki University of Technology

This thesis is concerned with recursive Bayesian estimation of non-linear dynamical systems, which can be modeled as discretely observed stochastic differential equations. The recursive real-time… (more)

Subjects/Keywords: Bayesian inference; continuous-discrete filtering; unscented Kalman filter; particle filter

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APA (6th Edition):

Särkkä, S. (2006). Recursive Bayesian Inference on Stochastic Differential Equations. (Thesis). Helsinki University of Technology. Retrieved from http://lib.tkk.fi/Diss/2006/isbn9512281279/

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):

Särkkä, Simo. “Recursive Bayesian Inference on Stochastic Differential Equations.” 2006. Thesis, Helsinki University of Technology. Accessed September 22, 2020. http://lib.tkk.fi/Diss/2006/isbn9512281279/.

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

MLA Handbook (7th Edition):

Särkkä, Simo. “Recursive Bayesian Inference on Stochastic Differential Equations.” 2006. Web. 22 Sep 2020.

Vancouver:

Särkkä S. Recursive Bayesian Inference on Stochastic Differential Equations. [Internet] [Thesis]. Helsinki University of Technology; 2006. [cited 2020 Sep 22]. Available from: http://lib.tkk.fi/Diss/2006/isbn9512281279/.

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

Council of Science Editors:

Särkkä S. Recursive Bayesian Inference on Stochastic Differential Equations. [Thesis]. Helsinki University of Technology; 2006. Available from: http://lib.tkk.fi/Diss/2006/isbn9512281279/

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


University of Alberta

20. 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 September 22, 2020. https://era.library.ualberta.ca/files/n009w369x.

MLA Handbook (7th Edition):

Shenoy, Arjun Vsiwanath. “Unconstrained nonlinear state estimation for chemical processes.” 2010. Web. 22 Sep 2020.

Vancouver:

Shenoy AV. Unconstrained nonlinear state estimation for chemical processes. [Internet] [Masters thesis]. University of Alberta; 2010. [cited 2020 Sep 22]. 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


Georgia Tech

21. Nakamura, Takuma. Multiple-hypothesis vision-based landing autonomy.

Degree: PhD, Aerospace Engineering, 2018, Georgia Tech

 Unmanned aerial vehicles (UAVs) need humans in the mission loop for many tasks, and landing is one of the tasks that typically involves a human… (more)

Subjects/Keywords: Sensor fusion; Kalman filter; Particle filter; SLAM; Computer vision

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APA (6th Edition):

Nakamura, T. (2018). Multiple-hypothesis vision-based landing autonomy. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62195

Chicago Manual of Style (16th Edition):

Nakamura, Takuma. “Multiple-hypothesis vision-based landing autonomy.” 2018. Doctoral Dissertation, Georgia Tech. Accessed September 22, 2020. http://hdl.handle.net/1853/62195.

MLA Handbook (7th Edition):

Nakamura, Takuma. “Multiple-hypothesis vision-based landing autonomy.” 2018. Web. 22 Sep 2020.

Vancouver:

Nakamura T. Multiple-hypothesis vision-based landing autonomy. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Sep 22]. Available from: http://hdl.handle.net/1853/62195.

Council of Science Editors:

Nakamura T. Multiple-hypothesis vision-based landing autonomy. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/62195


Penn State University

22. Chen, Meng. Dual Estimation in State Space Models with Violation to Normality: A Comparison between the Extended Kalman Filter and the Particle Filter.

Degree: 2019, Penn State University

 In the field of psychology and developmental science, researchers often study the change of some underlying latent construct over time. It is of interest both… (more)

Subjects/Keywords: state space model; Kalman filter; particle filter; dual estimation

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APA (6th Edition):

Chen, M. (2019). Dual Estimation in State Space Models with Violation to Normality: A Comparison between the Extended Kalman Filter and the Particle Filter. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/17297mxc681

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):

Chen, Meng. “Dual Estimation in State Space Models with Violation to Normality: A Comparison between the Extended Kalman Filter and the Particle Filter.” 2019. Thesis, Penn State University. Accessed September 22, 2020. https://submit-etda.libraries.psu.edu/catalog/17297mxc681.

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

MLA Handbook (7th Edition):

Chen, Meng. “Dual Estimation in State Space Models with Violation to Normality: A Comparison between the Extended Kalman Filter and the Particle Filter.” 2019. Web. 22 Sep 2020.

Vancouver:

Chen M. Dual Estimation in State Space Models with Violation to Normality: A Comparison between the Extended Kalman Filter and the Particle Filter. [Internet] [Thesis]. Penn State University; 2019. [cited 2020 Sep 22]. Available from: https://submit-etda.libraries.psu.edu/catalog/17297mxc681.

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

Council of Science Editors:

Chen M. Dual Estimation in State Space Models with Violation to Normality: A Comparison between the Extended Kalman Filter and the Particle Filter. [Thesis]. Penn State University; 2019. Available from: https://submit-etda.libraries.psu.edu/catalog/17297mxc681

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


McMaster University

23. Leach, James. ADVANCING SEQUENTIAL DATA ASSIMILATION METHODS FOR ENHANCED HYDROLOGIC FORECASTING IN SEMI-URBAN WATERSHEDS.

Degree: PhD, 2019, McMaster University

Accurate hydrologic forecasting is vital for proper water resource management. Practices that are impacted by these forecasts include power generation, reservoir management, agricultural water use,… (more)

Subjects/Keywords: Data Assimilation; Ensemble Forecasting; Ensemble Kalman FIlter; Particle Filter; Streamflow

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APA (6th Edition):

Leach, J. (2019). ADVANCING SEQUENTIAL DATA ASSIMILATION METHODS FOR ENHANCED HYDROLOGIC FORECASTING IN SEMI-URBAN WATERSHEDS. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/25083

Chicago Manual of Style (16th Edition):

Leach, James. “ADVANCING SEQUENTIAL DATA ASSIMILATION METHODS FOR ENHANCED HYDROLOGIC FORECASTING IN SEMI-URBAN WATERSHEDS.” 2019. Doctoral Dissertation, McMaster University. Accessed September 22, 2020. http://hdl.handle.net/11375/25083.

MLA Handbook (7th Edition):

Leach, James. “ADVANCING SEQUENTIAL DATA ASSIMILATION METHODS FOR ENHANCED HYDROLOGIC FORECASTING IN SEMI-URBAN WATERSHEDS.” 2019. Web. 22 Sep 2020.

Vancouver:

Leach J. ADVANCING SEQUENTIAL DATA ASSIMILATION METHODS FOR ENHANCED HYDROLOGIC FORECASTING IN SEMI-URBAN WATERSHEDS. [Internet] [Doctoral dissertation]. McMaster University; 2019. [cited 2020 Sep 22]. Available from: http://hdl.handle.net/11375/25083.

Council of Science Editors:

Leach J. ADVANCING SEQUENTIAL DATA ASSIMILATION METHODS FOR ENHANCED HYDROLOGIC FORECASTING IN SEMI-URBAN WATERSHEDS. [Doctoral Dissertation]. McMaster University; 2019. Available from: http://hdl.handle.net/11375/25083


Virginia Commonwealth University

24. 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://doi.org/10.25772/1BF9-H342 ; 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 September 22, 2020. https://doi.org/10.25772/1BF9-H342 ; 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. 22 Sep 2020.

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 2020 Sep 22]. Available from: https://doi.org/10.25772/1BF9-H342 ; 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://doi.org/10.25772/1BF9-H342 ; 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 Illinois – Urbana-Champaign

25. 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 September 22, 2020. 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. 22 Sep 2020.

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 2020 Sep 22]. 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 Tennessee – Knoxville

26. 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 September 22, 2020. 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. 22 Sep 2020.

Vancouver:

Collins JP. Comparison of Methods for Estimating Stochastic Volatility. [Internet] [Thesis]. University of Tennessee – Knoxville; 2013. [cited 2020 Sep 22]. 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

27. Tapiero Bernal, Juan Esteban. Bayesian Estimation For Tracking Of Spiraling Reentry Vehicles.

Degree: 2013, Marquette University

 This thesis presents a development of a physics-based dynamics model of a spiraling atmospheric reentry vehicle. An analysis of the trajectory characteristics, using elements from… (more)

Subjects/Keywords: Estimation; Extended Kalman filter; Modeling; Particle filter; Reentry; Tracking

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APA (6th Edition):

Tapiero Bernal, J. E. (2013). Bayesian Estimation For Tracking Of Spiraling Reentry Vehicles. (Thesis). Marquette University. Retrieved from https://epublications.marquette.edu/theses_open/203

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):

Tapiero Bernal, Juan Esteban. “Bayesian Estimation For Tracking Of Spiraling Reentry Vehicles.” 2013. Thesis, Marquette University. Accessed September 22, 2020. https://epublications.marquette.edu/theses_open/203.

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

MLA Handbook (7th Edition):

Tapiero Bernal, Juan Esteban. “Bayesian Estimation For Tracking Of Spiraling Reentry Vehicles.” 2013. Web. 22 Sep 2020.

Vancouver:

Tapiero Bernal JE. Bayesian Estimation For Tracking Of Spiraling Reentry Vehicles. [Internet] [Thesis]. Marquette University; 2013. [cited 2020 Sep 22]. Available from: https://epublications.marquette.edu/theses_open/203.

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

Council of Science Editors:

Tapiero Bernal JE. Bayesian Estimation For Tracking Of Spiraling Reentry Vehicles. [Thesis]. Marquette University; 2013. Available from: https://epublications.marquette.edu/theses_open/203

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


University of California – Berkeley

28. Lei, Jing. Non-linear Filtering for State Space Models - High-Dimensional Applications and Theoretical Results.

Degree: Statistics, 2010, University of California – Berkeley

 State space models are powerful modeling tools for stochastic dynamical systems and have been an important research area in the statistics community in the last… (more)

Subjects/Keywords: Statistics; chaotic dynamical systems; high dimension data; Kalman filter; particle filter; robustness; state space models

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APA (6th Edition):

Lei, J. (2010). Non-linear Filtering for State Space Models - High-Dimensional Applications and Theoretical Results. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/3tm9052d

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):

Lei, Jing. “Non-linear Filtering for State Space Models - High-Dimensional Applications and Theoretical Results.” 2010. Thesis, University of California – Berkeley. Accessed September 22, 2020. http://www.escholarship.org/uc/item/3tm9052d.

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

MLA Handbook (7th Edition):

Lei, Jing. “Non-linear Filtering for State Space Models - High-Dimensional Applications and Theoretical Results.” 2010. Web. 22 Sep 2020.

Vancouver:

Lei J. Non-linear Filtering for State Space Models - High-Dimensional Applications and Theoretical Results. [Internet] [Thesis]. University of California – Berkeley; 2010. [cited 2020 Sep 22]. Available from: http://www.escholarship.org/uc/item/3tm9052d.

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

Council of Science Editors:

Lei J. Non-linear Filtering for State Space Models - High-Dimensional Applications and Theoretical Results. [Thesis]. University of California – Berkeley; 2010. Available from: http://www.escholarship.org/uc/item/3tm9052d

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


Brigham Young University

29. 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 September 22, 2020. 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. 22 Sep 2020.

Vancouver:

Cannon BJ. Fault Detection for Unmanned Aerial Vehicles with Non-Redundant Sensors. [Internet] [Masters thesis]. Brigham Young University; 2014. [cited 2020 Sep 22]. 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 Illinois – Urbana-Champaign

30. Wang, Ren. Hybrid state estimation applications for joint traffic monitoring and incident detection.

Degree: PhD, Civil Engineering, 2015, University of Illinois – Urbana-Champaign

 This dissertation is motivated by the practical problems of highway traffic estimation and incident detection using measurements from various sensor types. It proposes a framework… (more)

Subjects/Keywords: Traffic state estimation; Traffic incident detection; Particle filter; Kalman filter; Hybrid state estimation

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

APA (6th Edition):

Wang, R. (2015). Hybrid state estimation applications for joint traffic monitoring and incident detection. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/88984

Chicago Manual of Style (16th Edition):

Wang, Ren. “Hybrid state estimation applications for joint traffic monitoring and incident detection.” 2015. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed September 22, 2020. http://hdl.handle.net/2142/88984.

MLA Handbook (7th Edition):

Wang, Ren. “Hybrid state estimation applications for joint traffic monitoring and incident detection.” 2015. Web. 22 Sep 2020.

Vancouver:

Wang R. Hybrid state estimation applications for joint traffic monitoring and incident detection. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2015. [cited 2020 Sep 22]. Available from: http://hdl.handle.net/2142/88984.

Council of Science Editors:

Wang R. Hybrid state estimation applications for joint traffic monitoring and incident detection. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/88984

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