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You searched for subject:(Bayesian filter). Showing records 1 – 30 of 75 total matches.

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University of Edinburgh

1. Zhong, Xionghu. Bayesian framework for multiple acoustic source tracking.

Degree: 2010, University of Edinburgh

 Acoustic source (speaker) tracking in the room environment plays an important role in many speech and audio applications such as multimedia, hearing aids and hands-free… (more)

Subjects/Keywords: 621.382; Bayesian filter; particle filtering; tracking

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APA (6th Edition):

Zhong, X. (2010). Bayesian framework for multiple acoustic source tracking. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/4752

Chicago Manual of Style (16th Edition):

Zhong, Xionghu. “Bayesian framework for multiple acoustic source tracking.” 2010. Doctoral Dissertation, University of Edinburgh. Accessed March 23, 2019. http://hdl.handle.net/1842/4752.

MLA Handbook (7th Edition):

Zhong, Xionghu. “Bayesian framework for multiple acoustic source tracking.” 2010. Web. 23 Mar 2019.

Vancouver:

Zhong X. Bayesian framework for multiple acoustic source tracking. [Internet] [Doctoral dissertation]. University of Edinburgh; 2010. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1842/4752.

Council of Science Editors:

Zhong X. Bayesian framework for multiple acoustic source tracking. [Doctoral Dissertation]. University of Edinburgh; 2010. Available from: http://hdl.handle.net/1842/4752


University of Waterloo

2. Datta Gupta, Syamantak. A Comparative Study of the Particle Filter and the Ensemble Kalman Filter.

Degree: 2009, University of Waterloo

 Non-linear Bayesian estimation, or estimation of the state of a non-linear stochastic system from a set of indirect noisy measurements is a problem encountered in… (more)

Subjects/Keywords: Bayesian estimation; non-linear filtering; particle filter; ensemble Kalman filter; Monte Carlo methods; Bayesian inference

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APA (6th Edition):

Datta Gupta, S. (2009). A Comparative Study of the Particle Filter and the Ensemble Kalman Filter. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/4503

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):

Datta Gupta, Syamantak. “A Comparative Study of the Particle Filter and the Ensemble Kalman Filter.” 2009. Thesis, University of Waterloo. Accessed March 23, 2019. http://hdl.handle.net/10012/4503.

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

MLA Handbook (7th Edition):

Datta Gupta, Syamantak. “A Comparative Study of the Particle Filter and the Ensemble Kalman Filter.” 2009. Web. 23 Mar 2019.

Vancouver:

Datta Gupta S. A Comparative Study of the Particle Filter and the Ensemble Kalman Filter. [Internet] [Thesis]. University of Waterloo; 2009. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/10012/4503.

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

Council of Science Editors:

Datta Gupta S. A Comparative Study of the Particle Filter and the Ensemble Kalman Filter. [Thesis]. University of Waterloo; 2009. Available from: http://hdl.handle.net/10012/4503

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

3. 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 March 23, 2019. 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. 23 Mar 2019.

Vancouver:

Särkkä S. Recursive Bayesian Inference on Stochastic Differential Equations. [Internet] [Thesis]. Helsinki University of Technology; 2006. [cited 2019 Mar 23]. 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


Delft University of Technology

4. Chitchian, M.M. 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. “Adapting Particle Filter Algorithms to the GPU Architecture:.” 2011. Masters Thesis, Delft University of Technology. Accessed March 23, 2019. http://resolver.tudelft.nl/uuid:9b11258e-cd9c-494d-bbb7-3b85c700b30f.

MLA Handbook (7th Edition):

Chitchian, M M. “Adapting Particle Filter Algorithms to the GPU Architecture:.” 2011. Web. 23 Mar 2019.

Vancouver:

Chitchian MM. Adapting Particle Filter Algorithms to the GPU Architecture:. [Internet] [Masters thesis]. Delft University of Technology; 2011. [cited 2019 Mar 23]. 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


George Mason University

5. Palvai, Anoop Kumar. Passive RF Localization Based on RSSI Using Non-linear Bayesian Estimation .

Degree: 2009, George Mason University

 RF localization has gained prominence because of its potential for supporting various position based applications. Passive RF Localization based on Received Signal Strength Indicator (RSSI)… (more)

Subjects/Keywords: Localization; Particle Filter; RSSI; Extended Kalman Filter; Non-Liner Bayesian Estimation; Sequential Importance Sampling

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

APA (6th Edition):

Palvai, A. K. (2009). Passive RF Localization Based on RSSI Using Non-linear Bayesian Estimation . (Thesis). George Mason University. Retrieved from http://hdl.handle.net/1920/3407

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):

Palvai, Anoop Kumar. “Passive RF Localization Based on RSSI Using Non-linear Bayesian Estimation .” 2009. Thesis, George Mason University. Accessed March 23, 2019. http://hdl.handle.net/1920/3407.

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

MLA Handbook (7th Edition):

Palvai, Anoop Kumar. “Passive RF Localization Based on RSSI Using Non-linear Bayesian Estimation .” 2009. Web. 23 Mar 2019.

Vancouver:

Palvai AK. Passive RF Localization Based on RSSI Using Non-linear Bayesian Estimation . [Internet] [Thesis]. George Mason University; 2009. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1920/3407.

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

Council of Science Editors:

Palvai AK. Passive RF Localization Based on RSSI Using Non-linear Bayesian Estimation . [Thesis]. George Mason University; 2009. Available from: http://hdl.handle.net/1920/3407

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


Delft University of Technology

6. Zilko, A.A. Non-Parametric Bayesian Networks (NPBNs) versus Ensemble Kalman Filter (EnKF) in Reservoir Simulation with non-Gaussian Measurement Noise:.

Degree: 2012, Delft University of Technology

 Lately, the objective of reservoir engineering is to optimize hydrocarbon recovery from a reservoir. To achieve that goal, a good knowledge of the subsurface properties… (more)

Subjects/Keywords: Ensemble Kalman Filter; Non-Parametric Bayesian Networks; Parameter Estimation; Reservoir Engineering; Reservoir Simulation; Bayesian Networks

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

APA (6th Edition):

Zilko, A. A. (2012). Non-Parametric Bayesian Networks (NPBNs) versus Ensemble Kalman Filter (EnKF) in Reservoir Simulation with non-Gaussian Measurement Noise:. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:97469901-4724-4c0b-851e-0eefb100adc8

Chicago Manual of Style (16th Edition):

Zilko, A A. “Non-Parametric Bayesian Networks (NPBNs) versus Ensemble Kalman Filter (EnKF) in Reservoir Simulation with non-Gaussian Measurement Noise:.” 2012. Masters Thesis, Delft University of Technology. Accessed March 23, 2019. http://resolver.tudelft.nl/uuid:97469901-4724-4c0b-851e-0eefb100adc8.

MLA Handbook (7th Edition):

Zilko, A A. “Non-Parametric Bayesian Networks (NPBNs) versus Ensemble Kalman Filter (EnKF) in Reservoir Simulation with non-Gaussian Measurement Noise:.” 2012. Web. 23 Mar 2019.

Vancouver:

Zilko AA. Non-Parametric Bayesian Networks (NPBNs) versus Ensemble Kalman Filter (EnKF) in Reservoir Simulation with non-Gaussian Measurement Noise:. [Internet] [Masters thesis]. Delft University of Technology; 2012. [cited 2019 Mar 23]. Available from: http://resolver.tudelft.nl/uuid:97469901-4724-4c0b-851e-0eefb100adc8.

Council of Science Editors:

Zilko AA. Non-Parametric Bayesian Networks (NPBNs) versus Ensemble Kalman Filter (EnKF) in Reservoir Simulation with non-Gaussian Measurement Noise:. [Masters Thesis]. Delft University of Technology; 2012. Available from: http://resolver.tudelft.nl/uuid:97469901-4724-4c0b-851e-0eefb100adc8


Brigham Young University

7. Havens, Russel William. Naive Bayesian Spam Filters for Log File Analysis.

Degree: MS, 2011, Brigham Young University

  As computer system usage grows in our world, system administrators need better visibility into the workings of computer systems, especially when those systems have… (more)

Subjects/Keywords: Russel Havens; log file analysis; Bayesian content filter; spam filter; SpamAssassin; SpamBayes; Bogofilter; filter effectiveness scale; fes; Computer Sciences

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APA (6th Edition):

Havens, R. W. (2011). Naive Bayesian Spam Filters for Log File Analysis. (Masters Thesis). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3813&context=etd

Chicago Manual of Style (16th Edition):

Havens, Russel William. “Naive Bayesian Spam Filters for Log File Analysis.” 2011. Masters Thesis, Brigham Young University. Accessed March 23, 2019. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3813&context=etd.

MLA Handbook (7th Edition):

Havens, Russel William. “Naive Bayesian Spam Filters for Log File Analysis.” 2011. Web. 23 Mar 2019.

Vancouver:

Havens RW. Naive Bayesian Spam Filters for Log File Analysis. [Internet] [Masters thesis]. Brigham Young University; 2011. [cited 2019 Mar 23]. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3813&context=etd.

Council of Science Editors:

Havens RW. Naive Bayesian Spam Filters for Log File Analysis. [Masters Thesis]. Brigham Young University; 2011. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3813&context=etd


University of Alberta

8. Shao, Xinguang. Particle Filter for Bayesian State Estimation and Its Application to Soft Sensor Development.

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

 For chemical engineering processes, state estimation plays a key role in various applications such as process monitoring, fault detection, process optimization and model based control.… (more)

Subjects/Keywords: Bayesian State Estimation; Particle Filter; Oil Sands Extraction; Soft Sensor

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

APA (6th Edition):

Shao, X. (2012). Particle Filter for Bayesian State Estimation and Its Application to Soft Sensor Development. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/707957685

Chicago Manual of Style (16th Edition):

Shao, Xinguang. “Particle Filter for Bayesian State Estimation and Its Application to Soft Sensor Development.” 2012. Doctoral Dissertation, University of Alberta. Accessed March 23, 2019. https://era.library.ualberta.ca/files/707957685.

MLA Handbook (7th Edition):

Shao, Xinguang. “Particle Filter for Bayesian State Estimation and Its Application to Soft Sensor Development.” 2012. Web. 23 Mar 2019.

Vancouver:

Shao X. Particle Filter for Bayesian State Estimation and Its Application to Soft Sensor Development. [Internet] [Doctoral dissertation]. University of Alberta; 2012. [cited 2019 Mar 23]. Available from: https://era.library.ualberta.ca/files/707957685.

Council of Science Editors:

Shao X. Particle Filter for Bayesian State Estimation and Its Application to Soft Sensor Development. [Doctoral Dissertation]. University of Alberta; 2012. Available from: https://era.library.ualberta.ca/files/707957685


Texas A&M University

9. Weisman, Ryan Michael 1984-. Nonlinear Transformations and Filtering Theory for Space Operations.

Degree: 2012, Texas A&M University

 Decisions for asset allocation and protection are predicated upon accurate knowledge of the current operating environment as well as correctly characterizing the evolution of the… (more)

Subjects/Keywords: filter initialization; uncertainty estimation; bayesian filtering; nonlinear estimation; space surveillance

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APA (6th Edition):

Weisman, R. M. 1. (2012). Nonlinear Transformations and Filtering Theory for Space Operations. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/148211

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):

Weisman, Ryan Michael 1984-. “Nonlinear Transformations and Filtering Theory for Space Operations.” 2012. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/148211.

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

MLA Handbook (7th Edition):

Weisman, Ryan Michael 1984-. “Nonlinear Transformations and Filtering Theory for Space Operations.” 2012. Web. 23 Mar 2019.

Vancouver:

Weisman RM1. Nonlinear Transformations and Filtering Theory for Space Operations. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/148211.

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

Council of Science Editors:

Weisman RM1. Nonlinear Transformations and Filtering Theory for Space Operations. [Thesis]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/148211

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

10. Alvares da Silva, Danilo. Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data.

Degree: 2018, TDX

 The statistical analysis of the information generated by medical follow-up is a very important challenge in the field of personalised medicine. As the evolutionary course… (more)

Subjects/Keywords: Bayesian analysis; Joint models; Personalised medicine; Particle filter; UNESCO::MATEMÁTICAS::Estadística

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

APA (6th Edition):

Alvares da Silva, D. (2018). Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data. (Thesis). TDX. Retrieved from http://hdl.handle.net/10550/59274

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):

Alvares da Silva, Danilo. “Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data.” 2018. Thesis, TDX. Accessed March 23, 2019. http://hdl.handle.net/10550/59274.

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

MLA Handbook (7th Edition):

Alvares da Silva, Danilo. “Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data.” 2018. Web. 23 Mar 2019.

Vancouver:

Alvares da Silva D. Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data. [Internet] [Thesis]. TDX; 2018. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/10550/59274.

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

Council of Science Editors:

Alvares da Silva D. Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data. [Thesis]. TDX; 2018. Available from: http://hdl.handle.net/10550/59274

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

11. Echeverri, Andrés F. Data Fusion for Vision-Based Robotic Platform Navigation.

Degree: 2016, Marquette University

 Data fusion has become an active research topic in recent years. Growing computational performance has allowed the use of redundant sensors to measure a single… (more)

Subjects/Keywords: Bayesian; Data Fusion; Kalman Filter; Tracking; UAV; Robotics

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APA (6th Edition):

Echeverri, A. F. (2016). Data Fusion for Vision-Based Robotic Platform Navigation. (Thesis). Marquette University. Retrieved from https://epublications.marquette.edu/theses_open/383

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):

Echeverri, Andrés F. “Data Fusion for Vision-Based Robotic Platform Navigation.” 2016. Thesis, Marquette University. Accessed March 23, 2019. https://epublications.marquette.edu/theses_open/383.

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

MLA Handbook (7th Edition):

Echeverri, Andrés F. “Data Fusion for Vision-Based Robotic Platform Navigation.” 2016. Web. 23 Mar 2019.

Vancouver:

Echeverri AF. Data Fusion for Vision-Based Robotic Platform Navigation. [Internet] [Thesis]. Marquette University; 2016. [cited 2019 Mar 23]. Available from: https://epublications.marquette.edu/theses_open/383.

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

Council of Science Editors:

Echeverri AF. Data Fusion for Vision-Based Robotic Platform Navigation. [Thesis]. Marquette University; 2016. Available from: https://epublications.marquette.edu/theses_open/383

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

12. Alvares da Silva, Danilo. Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data.

Degree: 2018, TDX

 The statistical analysis of the information generated by medical follow-up is a very important challenge in the field of personalised medicine. As the evolutionary course… (more)

Subjects/Keywords: Bayesian analysis; Joint models; Personalised medicine; Particle filter; UNESCO::MATEMÁTICAS::Estadística

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

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

APA (6th Edition):

Alvares da Silva, D. (2018). Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data. (Thesis). TDX. Retrieved from http://hdl.handle.net/10803/571460

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):

Alvares da Silva, Danilo. “Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data.” 2018. Thesis, TDX. Accessed March 23, 2019. http://hdl.handle.net/10803/571460.

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

MLA Handbook (7th Edition):

Alvares da Silva, Danilo. “Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data.” 2018. Web. 23 Mar 2019.

Vancouver:

Alvares da Silva D. Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data. [Internet] [Thesis]. TDX; 2018. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/10803/571460.

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

Council of Science Editors:

Alvares da Silva D. Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data. [Thesis]. TDX; 2018. Available from: http://hdl.handle.net/10803/571460

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

13. Ravet, Alexandre. Introducing contextual awareness within the state estimation process : Bayes filters with context-dependent time-heterogeneous distributions : Présentation de sensibilisation contextuelle dans le processus d'estimation d'état : Extension de Bayes filtres avec des distributions de temps hétérogènes dépendant du contexte.

Degree: Docteur es, Systèmes Embarqués et Robotique, 2015, Toulouse, INSA

 Ces travaux se focalisent sur une problématique fondamentale de la robotique autonome: l'estimation d'état. En effet, la plupart des approches actuelles permettant à un robot… (more)

Subjects/Keywords: Filtre bayésien; Système physique; Bayesian filter; Physical system; 004; 629.8

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APA (6th Edition):

Ravet, A. (2015). Introducing contextual awareness within the state estimation process : Bayes filters with context-dependent time-heterogeneous distributions : Présentation de sensibilisation contextuelle dans le processus d'estimation d'état : Extension de Bayes filtres avec des distributions de temps hétérogènes dépendant du contexte. (Doctoral Dissertation). Toulouse, INSA. Retrieved from http://www.theses.fr/2015ISAT0045

Chicago Manual of Style (16th Edition):

Ravet, Alexandre. “Introducing contextual awareness within the state estimation process : Bayes filters with context-dependent time-heterogeneous distributions : Présentation de sensibilisation contextuelle dans le processus d'estimation d'état : Extension de Bayes filtres avec des distributions de temps hétérogènes dépendant du contexte.” 2015. Doctoral Dissertation, Toulouse, INSA. Accessed March 23, 2019. http://www.theses.fr/2015ISAT0045.

MLA Handbook (7th Edition):

Ravet, Alexandre. “Introducing contextual awareness within the state estimation process : Bayes filters with context-dependent time-heterogeneous distributions : Présentation de sensibilisation contextuelle dans le processus d'estimation d'état : Extension de Bayes filtres avec des distributions de temps hétérogènes dépendant du contexte.” 2015. Web. 23 Mar 2019.

Vancouver:

Ravet A. Introducing contextual awareness within the state estimation process : Bayes filters with context-dependent time-heterogeneous distributions : Présentation de sensibilisation contextuelle dans le processus d'estimation d'état : Extension de Bayes filtres avec des distributions de temps hétérogènes dépendant du contexte. [Internet] [Doctoral dissertation]. Toulouse, INSA; 2015. [cited 2019 Mar 23]. Available from: http://www.theses.fr/2015ISAT0045.

Council of Science Editors:

Ravet A. Introducing contextual awareness within the state estimation process : Bayes filters with context-dependent time-heterogeneous distributions : Présentation de sensibilisation contextuelle dans le processus d'estimation d'état : Extension de Bayes filtres avec des distributions de temps hétérogènes dépendant du contexte. [Doctoral Dissertation]. Toulouse, INSA; 2015. Available from: http://www.theses.fr/2015ISAT0045


University of California – San Diego

14. Huang, Chun-Chia. State estimation with imperfect communications: escape time formulation and exact quantized-innovations filtering.

Degree: Engineering Sciences (Mechanical Engineering), 2015, University of California – San Diego

 The problem of state estimation for a linear, time-varying, gaussian system from measurements which are communicated over an imperfect channel is considered from several perspectives.… (more)

Subjects/Keywords: Mechanical engineering; Bayesian filtering; Escape time; Kalman filter; packet dropping; quantization

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APA (6th Edition):

Huang, C. (2015). State estimation with imperfect communications: escape time formulation and exact quantized-innovations filtering. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/9c82172m

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):

Huang, Chun-Chia. “State estimation with imperfect communications: escape time formulation and exact quantized-innovations filtering.” 2015. Thesis, University of California – San Diego. Accessed March 23, 2019. http://www.escholarship.org/uc/item/9c82172m.

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

MLA Handbook (7th Edition):

Huang, Chun-Chia. “State estimation with imperfect communications: escape time formulation and exact quantized-innovations filtering.” 2015. Web. 23 Mar 2019.

Vancouver:

Huang C. State estimation with imperfect communications: escape time formulation and exact quantized-innovations filtering. [Internet] [Thesis]. University of California – San Diego; 2015. [cited 2019 Mar 23]. Available from: http://www.escholarship.org/uc/item/9c82172m.

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

Council of Science Editors:

Huang C. State estimation with imperfect communications: escape time formulation and exact quantized-innovations filtering. [Thesis]. University of California – San Diego; 2015. Available from: http://www.escholarship.org/uc/item/9c82172m

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


University of Arizona

15. Woodard, Aaron Jacob. Bayesian Estimation of a Single Mass Concentration Within an Asteroid .

Degree: 2017, University of Arizona

 Orbit determination has long relied on the use of the Kalman filter, or specifically the extended Kalman filter, as a means of accurately navigating spacecraft.… (more)

Subjects/Keywords: Asteroid; Bayesian Estimation; Gravity Field; Sequential Monte Carlo Filter

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APA (6th Edition):

Woodard, A. J. (2017). Bayesian Estimation of a Single Mass Concentration Within an Asteroid . (Masters Thesis). University of Arizona. Retrieved from http://hdl.handle.net/10150/625702

Chicago Manual of Style (16th Edition):

Woodard, Aaron Jacob. “Bayesian Estimation of a Single Mass Concentration Within an Asteroid .” 2017. Masters Thesis, University of Arizona. Accessed March 23, 2019. http://hdl.handle.net/10150/625702.

MLA Handbook (7th Edition):

Woodard, Aaron Jacob. “Bayesian Estimation of a Single Mass Concentration Within an Asteroid .” 2017. Web. 23 Mar 2019.

Vancouver:

Woodard AJ. Bayesian Estimation of a Single Mass Concentration Within an Asteroid . [Internet] [Masters thesis]. University of Arizona; 2017. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/10150/625702.

Council of Science Editors:

Woodard AJ. Bayesian Estimation of a Single Mass Concentration Within an Asteroid . [Masters Thesis]. University of Arizona; 2017. Available from: http://hdl.handle.net/10150/625702


Vanderbilt University

16. 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 23, 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. 23 Mar 2019.

Vancouver:

Weng J. Dynamic Bayesian Network Based Fault Diagnosis on Nonlinear Dynamic Systems. [Internet] [Masters thesis]. Vanderbilt University; 2013. [cited 2019 Mar 23]. 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/ ;


University of Texas – Austin

17. Ramakrishnan, Anurekha. Predicting influenza hospitalizations.

Degree: Statistics, 2012, University of Texas – Austin

 Seasonal influenza epidemics are a major public health concern, causing three to five million cases of severe illness and about 250,000 to 500,000 deaths worldwide.… (more)

Subjects/Keywords: Bayesian estimation; Flu forecasting; Influenza hospitalization prediction; Kalman filter

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APA (6th Edition):

Ramakrishnan, A. (2012). Predicting influenza hospitalizations. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/26598

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):

Ramakrishnan, Anurekha. “Predicting influenza hospitalizations.” 2012. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/26598.

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

MLA Handbook (7th Edition):

Ramakrishnan, Anurekha. “Predicting influenza hospitalizations.” 2012. Web. 23 Mar 2019.

Vancouver:

Ramakrishnan A. Predicting influenza hospitalizations. [Internet] [Thesis]. University of Texas – Austin; 2012. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/26598.

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

Council of Science Editors:

Ramakrishnan A. Predicting influenza hospitalizations. [Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/26598

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


University of Minnesota

18. Nerurkar, Esha. Mobile Robot Localization Under Processing And Communication Constraints.

Degree: PhD, Computer Science, 2016, University of Minnesota

 Mobile robot localization is one of the most fundamental problems in robotics. For robots assisting humans in tasks such as surveillance, search and rescue, and… (more)

Subjects/Keywords: Bayesian estimation; Distributed processing; Kalman filter; Multi-robot; vision-inertial

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APA (6th Edition):

Nerurkar, E. (2016). Mobile Robot Localization Under Processing And Communication Constraints. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/180205

Chicago Manual of Style (16th Edition):

Nerurkar, Esha. “Mobile Robot Localization Under Processing And Communication Constraints.” 2016. Doctoral Dissertation, University of Minnesota. Accessed March 23, 2019. http://hdl.handle.net/11299/180205.

MLA Handbook (7th Edition):

Nerurkar, Esha. “Mobile Robot Localization Under Processing And Communication Constraints.” 2016. Web. 23 Mar 2019.

Vancouver:

Nerurkar E. Mobile Robot Localization Under Processing And Communication Constraints. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/11299/180205.

Council of Science Editors:

Nerurkar E. Mobile Robot Localization Under Processing And Communication Constraints. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/180205


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 23, 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. 23 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 23]. 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


University of Waterloo

20. Mathew, Manoj. Modeling and State Estimation of Lithium-Ion Battery Packs for Application in Battery Management Systems.

Degree: 2018, University of Waterloo

 As lithium-ion (Li-Ion) battery packs grow in popularity, so do the concerns of its safety, reliability, and cost. An efficient and robust battery management system… (more)

Subjects/Keywords: lithium-ion; state estimation; parameter estimaton; recursive bayesian filter

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APA (6th Edition):

Mathew, M. (2018). Modeling and State Estimation of Lithium-Ion Battery Packs for Application in Battery Management Systems. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13268

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):

Mathew, Manoj. “Modeling and State Estimation of Lithium-Ion Battery Packs for Application in Battery Management Systems.” 2018. Thesis, University of Waterloo. Accessed March 23, 2019. http://hdl.handle.net/10012/13268.

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

MLA Handbook (7th Edition):

Mathew, Manoj. “Modeling and State Estimation of Lithium-Ion Battery Packs for Application in Battery Management Systems.” 2018. Web. 23 Mar 2019.

Vancouver:

Mathew M. Modeling and State Estimation of Lithium-Ion Battery Packs for Application in Battery Management Systems. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/10012/13268.

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

Council of Science Editors:

Mathew M. Modeling and State Estimation of Lithium-Ion Battery Packs for Application in Battery Management Systems. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13268

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


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 23, 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. 23 Mar 2019.

Vancouver:

Qureshi M. Receiver-Based Algorithm for Bidirectional Nonlinear Satcom Channels. [Internet] [Doctoral dissertation]. University of Virginia; 2014. [cited 2019 Mar 23]. 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 Plymouth

22. Al-Saadony, Muhannad. Bayesian stochastic differential equation modelling with application to finance.

Degree: PhD, 2013, University of Plymouth

 In this thesis, we consider some popular stochastic differential equation models used in finance, such as the Vasicek Interest Rate model, the Heston model and… (more)

Subjects/Keywords: 519.2; Fractional Stochastic Differential Equation, Bayesian inference, Markov chain Monte Carlo, Sequential Monte carlo Methods, Particle Filter, Auxiliary Particle Filter.

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APA (6th Edition):

Al-Saadony, M. (2013). Bayesian stochastic differential equation modelling with application to finance. (Doctoral Dissertation). University of Plymouth. Retrieved from http://hdl.handle.net/10026.1/1530

Chicago Manual of Style (16th Edition):

Al-Saadony, Muhannad. “Bayesian stochastic differential equation modelling with application to finance.” 2013. Doctoral Dissertation, University of Plymouth. Accessed March 23, 2019. http://hdl.handle.net/10026.1/1530.

MLA Handbook (7th Edition):

Al-Saadony, Muhannad. “Bayesian stochastic differential equation modelling with application to finance.” 2013. Web. 23 Mar 2019.

Vancouver:

Al-Saadony M. Bayesian stochastic differential equation modelling with application to finance. [Internet] [Doctoral dissertation]. University of Plymouth; 2013. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/10026.1/1530.

Council of Science Editors:

Al-Saadony M. Bayesian stochastic differential equation modelling with application to finance. [Doctoral Dissertation]. University of Plymouth; 2013. Available from: http://hdl.handle.net/10026.1/1530

23. Champagne, Clara. Mathematical modeling and statistical inference to better understand arbovirus dynamics : Modélisation mathématique et inférence statistique pour une meilleure compréhension des dynamiques des arboviroses.

Degree: Docteur es, Mathématiques aux interfaces, 2018, Paris Saclay

L’importance et l’expansion des arboviroses comme la dengue ou le virus Zika nécessite des modèles pour mieux comprendre et prédire leurs dynamiques. La propagation vectorielle… (more)

Subjects/Keywords: Particle filter; Inférence bayésienne; Virus Zika; Dengue; Dengue fever; South-East asia; Particle filter; Bayesian inference; 579.2; 616.9; 00; 62; 92

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APA (6th Edition):

Champagne, C. (2018). Mathematical modeling and statistical inference to better understand arbovirus dynamics : Modélisation mathématique et inférence statistique pour une meilleure compréhension des dynamiques des arboviroses. (Doctoral Dissertation). Paris Saclay. Retrieved from http://www.theses.fr/2018SACLG006

Chicago Manual of Style (16th Edition):

Champagne, Clara. “Mathematical modeling and statistical inference to better understand arbovirus dynamics : Modélisation mathématique et inférence statistique pour une meilleure compréhension des dynamiques des arboviroses.” 2018. Doctoral Dissertation, Paris Saclay. Accessed March 23, 2019. http://www.theses.fr/2018SACLG006.

MLA Handbook (7th Edition):

Champagne, Clara. “Mathematical modeling and statistical inference to better understand arbovirus dynamics : Modélisation mathématique et inférence statistique pour une meilleure compréhension des dynamiques des arboviroses.” 2018. Web. 23 Mar 2019.

Vancouver:

Champagne C. Mathematical modeling and statistical inference to better understand arbovirus dynamics : Modélisation mathématique et inférence statistique pour une meilleure compréhension des dynamiques des arboviroses. [Internet] [Doctoral dissertation]. Paris Saclay; 2018. [cited 2019 Mar 23]. Available from: http://www.theses.fr/2018SACLG006.

Council of Science Editors:

Champagne C. Mathematical modeling and statistical inference to better understand arbovirus dynamics : Modélisation mathématique et inférence statistique pour une meilleure compréhension des dynamiques des arboviroses. [Doctoral Dissertation]. Paris Saclay; 2018. Available from: http://www.theses.fr/2018SACLG006


University of Cincinnati

24. Aull, Mark J. Comparison of Fault Detection Strategies on a Low Bypass Turbofan Engine Model.

Degree: MS, Engineering and Applied Science: Aerospace Engineering, 2011, University of Cincinnati

 Current diagnostics on most gas turbine engines involve off-line processing only. Since failures can cause serious safety and efficiency problems, such as elevated turbine temperatures… (more)

Subjects/Keywords: Aerospace Materials; Fault Diagnostics; Gas Turbine; Kalman Filter; Bayesian Network; Fuzzy Logic

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APA (6th Edition):

Aull, M. J. (2011). Comparison of Fault Detection Strategies on a Low Bypass Turbofan Engine Model. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321368833

Chicago Manual of Style (16th Edition):

Aull, Mark J. “Comparison of Fault Detection Strategies on a Low Bypass Turbofan Engine Model.” 2011. Masters Thesis, University of Cincinnati. Accessed March 23, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321368833.

MLA Handbook (7th Edition):

Aull, Mark J. “Comparison of Fault Detection Strategies on a Low Bypass Turbofan Engine Model.” 2011. Web. 23 Mar 2019.

Vancouver:

Aull MJ. Comparison of Fault Detection Strategies on a Low Bypass Turbofan Engine Model. [Internet] [Masters thesis]. University of Cincinnati; 2011. [cited 2019 Mar 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321368833.

Council of Science Editors:

Aull MJ. Comparison of Fault Detection Strategies on a Low Bypass Turbofan Engine Model. [Masters Thesis]. University of Cincinnati; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321368833


Temple University

25. Ackerman, Samuel. A Probabilistic Characterization of Shark Movement Using Location Tracking Data.

Degree: PhD, 2018, Temple University

Statistics

Our data consist of measurements of 22 sharks' movements within a 366-acre tidal basin. The measurements are made at irregular time points over a… (more)

Subjects/Keywords: Statistics; Biology; Computer science;

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APA (6th Edition):

Ackerman, S. (2018). A Probabilistic Characterization of Shark Movement Using Location Tracking Data. (Doctoral Dissertation). Temple University. Retrieved from http://digital.library.temple.edu/u?/p245801coll10,499173

Chicago Manual of Style (16th Edition):

Ackerman, Samuel. “A Probabilistic Characterization of Shark Movement Using Location Tracking Data.” 2018. Doctoral Dissertation, Temple University. Accessed March 23, 2019. http://digital.library.temple.edu/u?/p245801coll10,499173.

MLA Handbook (7th Edition):

Ackerman, Samuel. “A Probabilistic Characterization of Shark Movement Using Location Tracking Data.” 2018. Web. 23 Mar 2019.

Vancouver:

Ackerman S. A Probabilistic Characterization of Shark Movement Using Location Tracking Data. [Internet] [Doctoral dissertation]. Temple University; 2018. [cited 2019 Mar 23]. Available from: http://digital.library.temple.edu/u?/p245801coll10,499173.

Council of Science Editors:

Ackerman S. A Probabilistic Characterization of Shark Movement Using Location Tracking Data. [Doctoral Dissertation]. Temple University; 2018. Available from: http://digital.library.temple.edu/u?/p245801coll10,499173


University of Texas – Austin

26. Bond, Mark Arjun. Using the filter-forward backward sampling algorithm in second-order Bayesian latent growth modeling.

Degree: Statistics, 2016, University of Texas – Austin

 In educational and social science research, large-scale testing data are frequently collected longitudinally so that researchers can evaluate change over time. Researchers may then wish… (more)

Subjects/Keywords: MCMC; Markov chain Monte Carlo; Time series; Autoregression; Bayesian estimation; Latent growth modeling; Kalman filter

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APA (6th Edition):

Bond, M. A. (2016). Using the filter-forward backward sampling algorithm in second-order Bayesian latent growth modeling. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/47132

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):

Bond, Mark Arjun. “Using the filter-forward backward sampling algorithm in second-order Bayesian latent growth modeling.” 2016. Thesis, University of Texas – Austin. Accessed March 23, 2019. http://hdl.handle.net/2152/47132.

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

MLA Handbook (7th Edition):

Bond, Mark Arjun. “Using the filter-forward backward sampling algorithm in second-order Bayesian latent growth modeling.” 2016. Web. 23 Mar 2019.

Vancouver:

Bond MA. Using the filter-forward backward sampling algorithm in second-order Bayesian latent growth modeling. [Internet] [Thesis]. University of Texas – Austin; 2016. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2152/47132.

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

Council of Science Editors:

Bond MA. Using the filter-forward backward sampling algorithm in second-order Bayesian latent growth modeling. [Thesis]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/47132

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


University of British Columbia

27. Dou, Yiping. Dynamic Bayesian models for modelling environmental space-time fields .

Degree: 2008, University of British Columbia

 This thesis addresses spatial interpolation and temporal prediction using air pollution data by several space-time modelling approaches. Firstly, we implement the dynamic linear modelling (DLM)… (more)

Subjects/Keywords: Bayesian hierarchical modelling; Kalman filter; Dynamic linear modelling; Bayesian spatial prediction; MCMC algorithm; Gibbs sampling; Wishart distributions; Forward filtering; Backward sampling; Bayesian spatial prediction; Bayesian empirical orthogonal functions; Bayesian spatial prediction methods

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APA (6th Edition):

Dou, Y. (2008). Dynamic Bayesian models for modelling environmental space-time fields . (Thesis). University of British Columbia. Retrieved from http://hdl.handle.net/2429/634

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):

Dou, Yiping. “Dynamic Bayesian models for modelling environmental space-time fields .” 2008. Thesis, University of British Columbia. Accessed March 23, 2019. http://hdl.handle.net/2429/634.

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

MLA Handbook (7th Edition):

Dou, Yiping. “Dynamic Bayesian models for modelling environmental space-time fields .” 2008. Web. 23 Mar 2019.

Vancouver:

Dou Y. Dynamic Bayesian models for modelling environmental space-time fields . [Internet] [Thesis]. University of British Columbia; 2008. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/2429/634.

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

Council of Science Editors:

Dou Y. Dynamic Bayesian models for modelling environmental space-time fields . [Thesis]. University of British Columbia; 2008. Available from: http://hdl.handle.net/2429/634

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


Loughborough University

28. Daniyan, Abdullahi. Advanced signal processing techniques for multi-target tracking.

Degree: PhD, 2018, Loughborough University

 The multi-target tracking problem essentially involves the recursive joint estimation of the state of unknown and time-varying number of targets present in a tracking scene,… (more)

Subjects/Keywords: Target tracking; Bayesian inference; Bayesian estimation; Signal Processing; Kalman filter; Random finite sets; RFS; Particle filter; PHD filter; Probability hypothesis filter; CPHD filter; Sequential Monte Carlo; Game theory; Regret matching; Correlated equilibrium; Passive radar; Statistical signal processing; Probability; GLMB; Labelled random finite sets; Kalman gain; Poisson mixture; B-spline

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APA (6th Edition):

Daniyan, A. (2018). Advanced signal processing techniques for multi-target tracking. (Doctoral Dissertation). Loughborough University. Retrieved from https://dspace.lboro.ac.uk/2134/35277 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763466

Chicago Manual of Style (16th Edition):

Daniyan, Abdullahi. “Advanced signal processing techniques for multi-target tracking.” 2018. Doctoral Dissertation, Loughborough University. Accessed March 23, 2019. https://dspace.lboro.ac.uk/2134/35277 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763466.

MLA Handbook (7th Edition):

Daniyan, Abdullahi. “Advanced signal processing techniques for multi-target tracking.” 2018. Web. 23 Mar 2019.

Vancouver:

Daniyan A. Advanced signal processing techniques for multi-target tracking. [Internet] [Doctoral dissertation]. Loughborough University; 2018. [cited 2019 Mar 23]. Available from: https://dspace.lboro.ac.uk/2134/35277 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763466.

Council of Science Editors:

Daniyan A. Advanced signal processing techniques for multi-target tracking. [Doctoral Dissertation]. Loughborough University; 2018. Available from: https://dspace.lboro.ac.uk/2134/35277 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.763466


Texas A&M University

29. Lee, Deok-Jin. Nonlinear bayesian filtering with applications to estimation and navigation.

Degree: 2005, Texas A&M University

 In principle, general approaches to optimal nonlinear filtering can be described in a unified way from the recursive Bayesian approach. The central idea to this… (more)

Subjects/Keywords: statistical nonlinear filtering; estimation and navigation; Bayesian filter

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APA (6th Edition):

Lee, D. (2005). Nonlinear bayesian filtering with applications to estimation and navigation. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/2269

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):

Lee, Deok-Jin. “Nonlinear bayesian filtering with applications to estimation and navigation.” 2005. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/2269.

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

MLA Handbook (7th Edition):

Lee, Deok-Jin. “Nonlinear bayesian filtering with applications to estimation and navigation.” 2005. Web. 23 Mar 2019.

Vancouver:

Lee D. Nonlinear bayesian filtering with applications to estimation and navigation. [Internet] [Thesis]. Texas A&M University; 2005. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/2269.

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

Council of Science Editors:

Lee D. Nonlinear bayesian filtering with applications to estimation and navigation. [Thesis]. Texas A&M University; 2005. Available from: http://hdl.handle.net/1969.1/2269

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


University of Exeter

30. Christmas, Jacqueline. Robust spatio-temporal latent variable models.

Degree: PhD, 2011, University of Exeter

 Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA) are widely-used mathematical models for decomposing multivariate data. They capture spatial relationships between variables, but ignore… (more)

Subjects/Keywords: 005.3; Bayesian inference : variational approximation : Student-t : Principal Component Analysis : autoregression : Canonical Correlation Analysis : Kalman filter/smoother

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

APA (6th Edition):

Christmas, J. (2011). Robust spatio-temporal latent variable models. (Doctoral Dissertation). University of Exeter. Retrieved from http://hdl.handle.net/10036/3051

Chicago Manual of Style (16th Edition):

Christmas, Jacqueline. “Robust spatio-temporal latent variable models.” 2011. Doctoral Dissertation, University of Exeter. Accessed March 23, 2019. http://hdl.handle.net/10036/3051.

MLA Handbook (7th Edition):

Christmas, Jacqueline. “Robust spatio-temporal latent variable models.” 2011. Web. 23 Mar 2019.

Vancouver:

Christmas J. Robust spatio-temporal latent variable models. [Internet] [Doctoral dissertation]. University of Exeter; 2011. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/10036/3051.

Council of Science Editors:

Christmas J. Robust spatio-temporal latent variable models. [Doctoral Dissertation]. University of Exeter; 2011. Available from: http://hdl.handle.net/10036/3051

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