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You searched for subject:(Signal processing Statistical methods). Showing records 1 – 30 of 54526 total matches.

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Ryerson University

1. Arani, Maryam Nematollahi. Robust Image Labeling Using Conditional Random Fields.

Degree: 2017, Ryerson University

 Object recognition has become a central topic in computer vision applications such as image search, robotics and vehicle safety systems. However, it is a challenging… (more)

Subjects/Keywords: Image processing  – Digital technology  – Mathematical models; Image processing  – Statistical methods; Stochastic processes; Signal processing  – Statistical methods; Random fields

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

APA (6th Edition):

Arani, M. N. (2017). Robust Image Labeling Using Conditional Random Fields. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A6670

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):

Arani, Maryam Nematollahi. “Robust Image Labeling Using Conditional Random Fields.” 2017. Thesis, Ryerson University. Accessed January 19, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A6670.

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

MLA Handbook (7th Edition):

Arani, Maryam Nematollahi. “Robust Image Labeling Using Conditional Random Fields.” 2017. Web. 19 Jan 2020.

Vancouver:

Arani MN. Robust Image Labeling Using Conditional Random Fields. [Internet] [Thesis]. Ryerson University; 2017. [cited 2020 Jan 19]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A6670.

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

Council of Science Editors:

Arani MN. Robust Image Labeling Using Conditional Random Fields. [Thesis]. Ryerson University; 2017. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A6670

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


Oregon State University

2. Behmard, Hamid R. Nonperiodic sampling theorems and filter banks.

Degree: PhD, Mathematics, 1999, Oregon State University

 Sampling theorems provide exact interpolation formulas for bandlimited functions. They play a fundamental role in signal processing. A function is called bandlimited if its Fourier… (more)

Subjects/Keywords: Signal processing  – Statistical methods

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APA (6th Edition):

Behmard, H. R. (1999). Nonperiodic sampling theorems and filter banks. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/16323

Chicago Manual of Style (16th Edition):

Behmard, Hamid R. “Nonperiodic sampling theorems and filter banks.” 1999. Doctoral Dissertation, Oregon State University. Accessed January 19, 2020. http://hdl.handle.net/1957/16323.

MLA Handbook (7th Edition):

Behmard, Hamid R. “Nonperiodic sampling theorems and filter banks.” 1999. Web. 19 Jan 2020.

Vancouver:

Behmard HR. Nonperiodic sampling theorems and filter banks. [Internet] [Doctoral dissertation]. Oregon State University; 1999. [cited 2020 Jan 19]. Available from: http://hdl.handle.net/1957/16323.

Council of Science Editors:

Behmard HR. Nonperiodic sampling theorems and filter banks. [Doctoral Dissertation]. Oregon State University; 1999. Available from: http://hdl.handle.net/1957/16323


Michigan State University

3. Wang, Yingxu. Sample and hold functions and non-minimum-phase systems.

Degree: 2014, Michigan State University

Thesis M.S. Michigan State University. Engineering Mechanics - Master of Science 2014.

ABSTRACTSAMPLE AND HOLD FUNCTIONS AND NON-MINIMUM-PHASE SYSTEMSByYingxu WangWith the same initial condition, a… (more)

Subjects/Keywords: Signal processing – Digital techniques – Mathematics; Sampling (Statistics); Engineering – Statistical methods; Engineering

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APA (6th Edition):

Wang, Y. (2014). Sample and hold functions and non-minimum-phase systems. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:3014

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):

Wang, Yingxu. “Sample and hold functions and non-minimum-phase systems.” 2014. Thesis, Michigan State University. Accessed January 19, 2020. http://etd.lib.msu.edu/islandora/object/etd:3014.

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

MLA Handbook (7th Edition):

Wang, Yingxu. “Sample and hold functions and non-minimum-phase systems.” 2014. Web. 19 Jan 2020.

Vancouver:

Wang Y. Sample and hold functions and non-minimum-phase systems. [Internet] [Thesis]. Michigan State University; 2014. [cited 2020 Jan 19]. Available from: http://etd.lib.msu.edu/islandora/object/etd:3014.

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

Council of Science Editors:

Wang Y. Sample and hold functions and non-minimum-phase systems. [Thesis]. Michigan State University; 2014. Available from: http://etd.lib.msu.edu/islandora/object/etd:3014

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


Hong Kong University of Science and Technology

4. Fung, Carrson Chee-Ho. Eigensystem based techniques for blind channel estimation and equalization.

Degree: 2005, Hong Kong University of Science and Technology

 Channel estimation and equalization form an integral part of modern communi-cation systems. Proper equalizer design can counteract channel distortions such as intersymbol interference (ISI), additive… (more)

Subjects/Keywords: Signal processing  – Statistical methods ; Eigenfunctions

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APA (6th Edition):

Fung, C. C. (2005). Eigensystem based techniques for blind channel estimation and equalization. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-2462 ; https://doi.org/10.14711/thesis-b864006 ; http://repository.ust.hk/ir/bitstream/1783.1-2462/1/th_redirect.html

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):

Fung, Carrson Chee-Ho. “Eigensystem based techniques for blind channel estimation and equalization.” 2005. Thesis, Hong Kong University of Science and Technology. Accessed January 19, 2020. http://repository.ust.hk/ir/Record/1783.1-2462 ; https://doi.org/10.14711/thesis-b864006 ; http://repository.ust.hk/ir/bitstream/1783.1-2462/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Fung, Carrson Chee-Ho. “Eigensystem based techniques for blind channel estimation and equalization.” 2005. Web. 19 Jan 2020.

Vancouver:

Fung CC. Eigensystem based techniques for blind channel estimation and equalization. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2005. [cited 2020 Jan 19]. Available from: http://repository.ust.hk/ir/Record/1783.1-2462 ; https://doi.org/10.14711/thesis-b864006 ; http://repository.ust.hk/ir/bitstream/1783.1-2462/1/th_redirect.html.

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

Council of Science Editors:

Fung CC. Eigensystem based techniques for blind channel estimation and equalization. [Thesis]. Hong Kong University of Science and Technology; 2005. Available from: http://repository.ust.hk/ir/Record/1783.1-2462 ; https://doi.org/10.14711/thesis-b864006 ; http://repository.ust.hk/ir/bitstream/1783.1-2462/1/th_redirect.html

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


Columbia University

5. Elmas, Abdulkadir. Topics in Signal Processing: applications in genomics and genetics.

Degree: 2016, Columbia University

 The information in genomic or genetic data is influenced by various complex processes and appropriate mathematical modeling is required for studying the underlying processes and… (more)

Subjects/Keywords: Signal processing; Signal processing – Statistical methods; Genetics – Data processing; Genomics – Data processing; Bioinformatics; Transcription factors; Electrical engineering

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APA (6th Edition):

Elmas, A. (2016). Topics in Signal Processing: applications in genomics and genetics. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D81Z44NP

Chicago Manual of Style (16th Edition):

Elmas, Abdulkadir. “Topics in Signal Processing: applications in genomics and genetics.” 2016. Doctoral Dissertation, Columbia University. Accessed January 19, 2020. https://doi.org/10.7916/D81Z44NP.

MLA Handbook (7th Edition):

Elmas, Abdulkadir. “Topics in Signal Processing: applications in genomics and genetics.” 2016. Web. 19 Jan 2020.

Vancouver:

Elmas A. Topics in Signal Processing: applications in genomics and genetics. [Internet] [Doctoral dissertation]. Columbia University; 2016. [cited 2020 Jan 19]. Available from: https://doi.org/10.7916/D81Z44NP.

Council of Science Editors:

Elmas A. Topics in Signal Processing: applications in genomics and genetics. [Doctoral Dissertation]. Columbia University; 2016. Available from: https://doi.org/10.7916/D81Z44NP


University of Michigan

6. Jin, Curtis. New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media.

Degree: PhD, Electrical Engineering: Systems, 2014, University of Michigan

 Scattering hinders the passage of light through random media and consequently limits the usefulness of optical techniques for sensing and imaging. Thus, methods for increasing… (more)

Subjects/Keywords: Wave Propagation; Scattering; Random Matrix Theory; Numerical Methods; Iterative Methods; Statistical Signal Processing; Electrical Engineering; Engineering; Science

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APA (6th Edition):

Jin, C. (2014). New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/107051

Chicago Manual of Style (16th Edition):

Jin, Curtis. “New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media.” 2014. Doctoral Dissertation, University of Michigan. Accessed January 19, 2020. http://hdl.handle.net/2027.42/107051.

MLA Handbook (7th Edition):

Jin, Curtis. “New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media.” 2014. Web. 19 Jan 2020.

Vancouver:

Jin C. New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media. [Internet] [Doctoral dissertation]. University of Michigan; 2014. [cited 2020 Jan 19]. Available from: http://hdl.handle.net/2027.42/107051.

Council of Science Editors:

Jin C. New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media. [Doctoral Dissertation]. University of Michigan; 2014. Available from: http://hdl.handle.net/2027.42/107051

7. Archer, Cynthia. A framework for representing non-stationary data with mixtures of linear models.

Degree: PhD, 2002, Oregon Health Sciences University

Subjects/Keywords: Signal processing  – Digital techniques  – Mathematics; Signal processing  – Statistical methods; Principal components analysis

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APA (6th Edition):

Archer, C. (2002). A framework for representing non-stationary data with mixtures of linear models. (Doctoral Dissertation). Oregon Health Sciences University. Retrieved from doi:10.6083/M47P8WB5 ; http://digitalcommons.ohsu.edu/etd/176

Chicago Manual of Style (16th Edition):

Archer, Cynthia. “A framework for representing non-stationary data with mixtures of linear models.” 2002. Doctoral Dissertation, Oregon Health Sciences University. Accessed January 19, 2020. doi:10.6083/M47P8WB5 ; http://digitalcommons.ohsu.edu/etd/176.

MLA Handbook (7th Edition):

Archer, Cynthia. “A framework for representing non-stationary data with mixtures of linear models.” 2002. Web. 19 Jan 2020.

Vancouver:

Archer C. A framework for representing non-stationary data with mixtures of linear models. [Internet] [Doctoral dissertation]. Oregon Health Sciences University; 2002. [cited 2020 Jan 19]. Available from: doi:10.6083/M47P8WB5 ; http://digitalcommons.ohsu.edu/etd/176.

Council of Science Editors:

Archer C. A framework for representing non-stationary data with mixtures of linear models. [Doctoral Dissertation]. Oregon Health Sciences University; 2002. Available from: doi:10.6083/M47P8WB5 ; http://digitalcommons.ohsu.edu/etd/176


University of Hong Kong

8. Vong, Chun-yin. Performance study of uniform sampling digital phase-locked loopsfor [Pi]/4-differentially encoded quaternary phase-shift keying.

Degree: M. Phil., 1998, University of Hong Kong

published_or_final_version

Electrical and Electronic Engineering

Master

Master of Philosophy

Subjects/Keywords: Demodulation (Electronics); Signal processing - Statistical methods.; Phase-locked loops.

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APA (6th Edition):

Vong, C. (1998). Performance study of uniform sampling digital phase-locked loopsfor [Pi]/4-differentially encoded quaternary phase-shift keying. (Masters Thesis). University of Hong Kong. Retrieved from Vong, C. [黃俊賢]. (1998). Performance study of uniform sampling digital phase-locked loops for [Pi]/4-differentially encoded quaternary phase-shift keying. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3122181 ; http://dx.doi.org/10.5353/th_b3122181 ; http://hdl.handle.net/10722/34143

Chicago Manual of Style (16th Edition):

Vong, Chun-yin. “Performance study of uniform sampling digital phase-locked loopsfor [Pi]/4-differentially encoded quaternary phase-shift keying.” 1998. Masters Thesis, University of Hong Kong. Accessed January 19, 2020. Vong, C. [黃俊賢]. (1998). Performance study of uniform sampling digital phase-locked loops for [Pi]/4-differentially encoded quaternary phase-shift keying. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3122181 ; http://dx.doi.org/10.5353/th_b3122181 ; http://hdl.handle.net/10722/34143.

MLA Handbook (7th Edition):

Vong, Chun-yin. “Performance study of uniform sampling digital phase-locked loopsfor [Pi]/4-differentially encoded quaternary phase-shift keying.” 1998. Web. 19 Jan 2020.

Vancouver:

Vong C. Performance study of uniform sampling digital phase-locked loopsfor [Pi]/4-differentially encoded quaternary phase-shift keying. [Internet] [Masters thesis]. University of Hong Kong; 1998. [cited 2020 Jan 19]. Available from: Vong, C. [黃俊賢]. (1998). Performance study of uniform sampling digital phase-locked loops for [Pi]/4-differentially encoded quaternary phase-shift keying. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3122181 ; http://dx.doi.org/10.5353/th_b3122181 ; http://hdl.handle.net/10722/34143.

Council of Science Editors:

Vong C. Performance study of uniform sampling digital phase-locked loopsfor [Pi]/4-differentially encoded quaternary phase-shift keying. [Masters Thesis]. University of Hong Kong; 1998. Available from: Vong, C. [黃俊賢]. (1998). Performance study of uniform sampling digital phase-locked loops for [Pi]/4-differentially encoded quaternary phase-shift keying. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3122181 ; http://dx.doi.org/10.5353/th_b3122181 ; http://hdl.handle.net/10722/34143


University of Hong Kong

9. 鄒月嫻; Zou, Yuexian. Robust statistics based adaptive filtering algorithms for impulsive noise suppression.

Degree: PhD, 2000, University of Hong Kong

 (Uncorrected OCR) Abstract Abstract of thesis entitled Robust Statistics Based Adaptive Filtering Algorithms For Impulsive Noise Suppression Submitted by Yuexian Zou for the degree of… (more)

Subjects/Keywords: Robust statistics.; Adaptive filters.; Signal processing - Statistical methods.

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APA (6th Edition):

鄒月嫻; Zou, Y. (2000). Robust statistics based adaptive filtering algorithms for impulsive noise suppression. (Doctoral Dissertation). University of Hong Kong. Retrieved from http://hdl.handle.net/10722/27149

Chicago Manual of Style (16th Edition):

鄒月嫻; Zou, Yuexian. “Robust statistics based adaptive filtering algorithms for impulsive noise suppression.” 2000. Doctoral Dissertation, University of Hong Kong. Accessed January 19, 2020. http://hdl.handle.net/10722/27149.

MLA Handbook (7th Edition):

鄒月嫻; Zou, Yuexian. “Robust statistics based adaptive filtering algorithms for impulsive noise suppression.” 2000. Web. 19 Jan 2020.

Vancouver:

鄒月嫻; Zou Y. Robust statistics based adaptive filtering algorithms for impulsive noise suppression. [Internet] [Doctoral dissertation]. University of Hong Kong; 2000. [cited 2020 Jan 19]. Available from: http://hdl.handle.net/10722/27149.

Council of Science Editors:

鄒月嫻; Zou Y. Robust statistics based adaptive filtering algorithms for impulsive noise suppression. [Doctoral Dissertation]. University of Hong Kong; 2000. Available from: http://hdl.handle.net/10722/27149


University of Hong Kong

10. Lau, Wing-yi. New recursive parameter estimation algorithms in impulsive noise environment with application to frequency estimation and systemidentification.

Degree: M. Phil., 2006, University of Hong Kong

published_or_final_version

abstract

Electrical and Electronic Engineering

Master

Master of Philosophy

Advisors/Committee Members: Chan, SC, Leung, CH.

Subjects/Keywords: Algorithms.; Parameter estimation.; Signal processing - Statistical methods.

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APA (6th Edition):

Lau, W. (2006). New recursive parameter estimation algorithms in impulsive noise environment with application to frequency estimation and systemidentification. (Masters Thesis). University of Hong Kong. Retrieved from Lau, W. [劉穎兒]. (2006). New recursive parameter estimation algorithms in impulsive noise environment with application to frequency estimation and system identification. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3759586 ; http://dx.doi.org/10.5353/th_b3759586 ; http://hdl.handle.net/10722/51460

Chicago Manual of Style (16th Edition):

Lau, Wing-yi. “New recursive parameter estimation algorithms in impulsive noise environment with application to frequency estimation and systemidentification.” 2006. Masters Thesis, University of Hong Kong. Accessed January 19, 2020. Lau, W. [劉穎兒]. (2006). New recursive parameter estimation algorithms in impulsive noise environment with application to frequency estimation and system identification. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3759586 ; http://dx.doi.org/10.5353/th_b3759586 ; http://hdl.handle.net/10722/51460.

MLA Handbook (7th Edition):

Lau, Wing-yi. “New recursive parameter estimation algorithms in impulsive noise environment with application to frequency estimation and systemidentification.” 2006. Web. 19 Jan 2020.

Vancouver:

Lau W. New recursive parameter estimation algorithms in impulsive noise environment with application to frequency estimation and systemidentification. [Internet] [Masters thesis]. University of Hong Kong; 2006. [cited 2020 Jan 19]. Available from: Lau, W. [劉穎兒]. (2006). New recursive parameter estimation algorithms in impulsive noise environment with application to frequency estimation and system identification. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3759586 ; http://dx.doi.org/10.5353/th_b3759586 ; http://hdl.handle.net/10722/51460.

Council of Science Editors:

Lau W. New recursive parameter estimation algorithms in impulsive noise environment with application to frequency estimation and systemidentification. [Masters Thesis]. University of Hong Kong; 2006. Available from: Lau, W. [劉穎兒]. (2006). New recursive parameter estimation algorithms in impulsive noise environment with application to frequency estimation and system identification. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b3759586 ; http://dx.doi.org/10.5353/th_b3759586 ; http://hdl.handle.net/10722/51460


Arizona State University

11. Dutson, Karl J. Target Tracking in Environments of Rapidly Changing Clutter.

Degree: Electrical Engineering, 2015, Arizona State University

 Tracking targets in the presence of clutter is inevitable, and presents many challenges. Additionally, rapid, drastic changes in clutter density between different environments or scenarios… (more)

Subjects/Keywords: Electrical engineering; Statistics; Computer science; Clutter Mitigation; Electrical Engineering; Interacting Multiple Model; Monte Carlo Methods; Radar Target Tracking; Statistical Signal Processing

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APA (6th Edition):

Dutson, K. J. (2015). Target Tracking in Environments of Rapidly Changing Clutter. (Masters Thesis). Arizona State University. Retrieved from http://repository.asu.edu/items/29894

Chicago Manual of Style (16th Edition):

Dutson, Karl J. “Target Tracking in Environments of Rapidly Changing Clutter.” 2015. Masters Thesis, Arizona State University. Accessed January 19, 2020. http://repository.asu.edu/items/29894.

MLA Handbook (7th Edition):

Dutson, Karl J. “Target Tracking in Environments of Rapidly Changing Clutter.” 2015. Web. 19 Jan 2020.

Vancouver:

Dutson KJ. Target Tracking in Environments of Rapidly Changing Clutter. [Internet] [Masters thesis]. Arizona State University; 2015. [cited 2020 Jan 19]. Available from: http://repository.asu.edu/items/29894.

Council of Science Editors:

Dutson KJ. Target Tracking in Environments of Rapidly Changing Clutter. [Masters Thesis]. Arizona State University; 2015. Available from: http://repository.asu.edu/items/29894


University of Southern California

12. Rozgić, Viktor. Statistical inference for dynamical, interacting multi-object systems with emphasis on human small group interactions.

Degree: PhD, Electrical Engineering, 2011, University of Southern California

 In this dissertation we propose contributions that address the problems in behavioral signal processing for small-group interactions from three important perspectives. We propose algorithmic contributions… (more)

Subjects/Keywords: statistical inference; multi-modal signal processing; behavioral signal processing

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APA (6th Edition):

Rozgić, V. (2011). Statistical inference for dynamical, interacting multi-object systems with emphasis on human small group interactions. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/653978/rec/6042

Chicago Manual of Style (16th Edition):

Rozgić, Viktor. “Statistical inference for dynamical, interacting multi-object systems with emphasis on human small group interactions.” 2011. Doctoral Dissertation, University of Southern California. Accessed January 19, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/653978/rec/6042.

MLA Handbook (7th Edition):

Rozgić, Viktor. “Statistical inference for dynamical, interacting multi-object systems with emphasis on human small group interactions.” 2011. Web. 19 Jan 2020.

Vancouver:

Rozgić V. Statistical inference for dynamical, interacting multi-object systems with emphasis on human small group interactions. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2020 Jan 19]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/653978/rec/6042.

Council of Science Editors:

Rozgić V. Statistical inference for dynamical, interacting multi-object systems with emphasis on human small group interactions. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/653978/rec/6042


Cornell University

13. Ozil, Ipek. System Identification Of Dynamical Models For Signals Related To The Human Use Of Ethanol .

Degree: 2014, Cornell University

 The influence of genetics on the risk for alcoholism is a major theme in alcoholism research. Genetic research depends on phenotyping. However, accurate phenotyping of… (more)

Subjects/Keywords: Statistical signal processing; Expectation maximization; System identification

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APA (6th Edition):

Ozil, I. (2014). System Identification Of Dynamical Models For Signals Related To The Human Use Of Ethanol . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/38828

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):

Ozil, Ipek. “System Identification Of Dynamical Models For Signals Related To The Human Use Of Ethanol .” 2014. Thesis, Cornell University. Accessed January 19, 2020. http://hdl.handle.net/1813/38828.

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

MLA Handbook (7th Edition):

Ozil, Ipek. “System Identification Of Dynamical Models For Signals Related To The Human Use Of Ethanol .” 2014. Web. 19 Jan 2020.

Vancouver:

Ozil I. System Identification Of Dynamical Models For Signals Related To The Human Use Of Ethanol . [Internet] [Thesis]. Cornell University; 2014. [cited 2020 Jan 19]. Available from: http://hdl.handle.net/1813/38828.

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

Council of Science Editors:

Ozil I. System Identification Of Dynamical Models For Signals Related To The Human Use Of Ethanol . [Thesis]. Cornell University; 2014. Available from: http://hdl.handle.net/1813/38828

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


University of New South Wales

14. Cassidy, Benjamin. Statistical signal processing methods for imaging brain activity.

Degree: Electrical Engineering & Telecommunications, 2014, University of New South Wales

 Functional neuroimaging involves the study of cognitive scientific questions by measuring and modelling brain activity, using techniques such as Functional Magnetic Resonance Imaging (fMRI) and… (more)

Subjects/Keywords: Magnetoencephalography; Statistical signal processing; Brain imaging; FMRI

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APA (6th Edition):

Cassidy, B. (2014). Statistical signal processing methods for imaging brain activity. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/53487 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12182/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Cassidy, Benjamin. “Statistical signal processing methods for imaging brain activity.” 2014. Doctoral Dissertation, University of New South Wales. Accessed January 19, 2020. http://handle.unsw.edu.au/1959.4/53487 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12182/SOURCE02?view=true.

MLA Handbook (7th Edition):

Cassidy, Benjamin. “Statistical signal processing methods for imaging brain activity.” 2014. Web. 19 Jan 2020.

Vancouver:

Cassidy B. Statistical signal processing methods for imaging brain activity. [Internet] [Doctoral dissertation]. University of New South Wales; 2014. [cited 2020 Jan 19]. Available from: http://handle.unsw.edu.au/1959.4/53487 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12182/SOURCE02?view=true.

Council of Science Editors:

Cassidy B. Statistical signal processing methods for imaging brain activity. [Doctoral Dissertation]. University of New South Wales; 2014. Available from: http://handle.unsw.edu.au/1959.4/53487 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12182/SOURCE02?view=true


Ryerson University

15. Manafi, Shirin. A two-stage normalization method for robust differential expression analysis in microarray experiments.

Degree: 2014, Ryerson University

 In this research, we introduce an approach to improve the reliability of genetic data analysis. Consistency of the results obtained from microarray data analysis strongly… (more)

Subjects/Keywords: DNA microarrays  – Data processing.; Genomics  – Statistical methods.

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

APA (6th Edition):

Manafi, S. (2014). A two-stage normalization method for robust differential expression analysis in microarray experiments. (Thesis). Ryerson University. Retrieved from https://digital.library.ryerson.ca/islandora/object/RULA%3A3367

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):

Manafi, Shirin. “A two-stage normalization method for robust differential expression analysis in microarray experiments.” 2014. Thesis, Ryerson University. Accessed January 19, 2020. https://digital.library.ryerson.ca/islandora/object/RULA%3A3367.

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

MLA Handbook (7th Edition):

Manafi, Shirin. “A two-stage normalization method for robust differential expression analysis in microarray experiments.” 2014. Web. 19 Jan 2020.

Vancouver:

Manafi S. A two-stage normalization method for robust differential expression analysis in microarray experiments. [Internet] [Thesis]. Ryerson University; 2014. [cited 2020 Jan 19]. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3367.

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

Council of Science Editors:

Manafi S. A two-stage normalization method for robust differential expression analysis in microarray experiments. [Thesis]. Ryerson University; 2014. Available from: https://digital.library.ryerson.ca/islandora/object/RULA%3A3367

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


Columbia University

16. Wang, Wei. On Model-Selection and Applications of Multilevel Models in Survey and Causal Inference.

Degree: 2016, Columbia University

 This thesis includes three parts. The overarching theme is how to analyze multilevel structured datasets, particularly in the areas of survey and causal inference. The… (more)

Subjects/Keywords: Social sciences – Statistical methods – Data processing; Statistics

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APA (6th Edition):

Wang, W. (2016). On Model-Selection and Applications of Multilevel Models in Survey and Causal Inference. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8571C4Q

Chicago Manual of Style (16th Edition):

Wang, Wei. “On Model-Selection and Applications of Multilevel Models in Survey and Causal Inference.” 2016. Doctoral Dissertation, Columbia University. Accessed January 19, 2020. https://doi.org/10.7916/D8571C4Q.

MLA Handbook (7th Edition):

Wang, Wei. “On Model-Selection and Applications of Multilevel Models in Survey and Causal Inference.” 2016. Web. 19 Jan 2020.

Vancouver:

Wang W. On Model-Selection and Applications of Multilevel Models in Survey and Causal Inference. [Internet] [Doctoral dissertation]. Columbia University; 2016. [cited 2020 Jan 19]. Available from: https://doi.org/10.7916/D8571C4Q.

Council of Science Editors:

Wang W. On Model-Selection and Applications of Multilevel Models in Survey and Causal Inference. [Doctoral Dissertation]. Columbia University; 2016. Available from: https://doi.org/10.7916/D8571C4Q


Hong Kong University of Science and Technology

17. Ding, Dong. Statistical process control based on ordinal data.

Degree: 2015, Hong Kong University of Science and Technology

 Quality is a critical keyword in almost all industries. Quality improvement is always the pursuit of a successful business. To reduce variability is a basic… (more)

Subjects/Keywords: Process control ; Data processing ; Statistical methods

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APA (6th Edition):

Ding, D. (2015). Statistical process control based on ordinal data. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-86321 ; https://doi.org/10.14711/thesis-b1514504 ; http://repository.ust.hk/ir/bitstream/1783.1-86321/1/th_redirect.html

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):

Ding, Dong. “Statistical process control based on ordinal data.” 2015. Thesis, Hong Kong University of Science and Technology. Accessed January 19, 2020. http://repository.ust.hk/ir/Record/1783.1-86321 ; https://doi.org/10.14711/thesis-b1514504 ; http://repository.ust.hk/ir/bitstream/1783.1-86321/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Ding, Dong. “Statistical process control based on ordinal data.” 2015. Web. 19 Jan 2020.

Vancouver:

Ding D. Statistical process control based on ordinal data. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2015. [cited 2020 Jan 19]. Available from: http://repository.ust.hk/ir/Record/1783.1-86321 ; https://doi.org/10.14711/thesis-b1514504 ; http://repository.ust.hk/ir/bitstream/1783.1-86321/1/th_redirect.html.

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

Council of Science Editors:

Ding D. Statistical process control based on ordinal data. [Thesis]. Hong Kong University of Science and Technology; 2015. Available from: http://repository.ust.hk/ir/Record/1783.1-86321 ; https://doi.org/10.14711/thesis-b1514504 ; http://repository.ust.hk/ir/bitstream/1783.1-86321/1/th_redirect.html

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


University of Cambridge

18. Peeling, Paul Halliday. Bayesian methods in music modelling.

Degree: PhD, 2011, University of Cambridge

 This thesis presents several hierarchical generative Bayesian models of musical signals designed to improve the accuracy of existing multiple pitch detection systems and other musical… (more)

Subjects/Keywords: 780; Music modelling; Signal processing; Bayesian methods

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

APA (6th Edition):

Peeling, P. H. (2011). Bayesian methods in music modelling. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/237236 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.541860

Chicago Manual of Style (16th Edition):

Peeling, Paul Halliday. “Bayesian methods in music modelling.” 2011. Doctoral Dissertation, University of Cambridge. Accessed January 19, 2020. https://www.repository.cam.ac.uk/handle/1810/237236 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.541860.

MLA Handbook (7th Edition):

Peeling, Paul Halliday. “Bayesian methods in music modelling.” 2011. Web. 19 Jan 2020.

Vancouver:

Peeling PH. Bayesian methods in music modelling. [Internet] [Doctoral dissertation]. University of Cambridge; 2011. [cited 2020 Jan 19]. Available from: https://www.repository.cam.ac.uk/handle/1810/237236 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.541860.

Council of Science Editors:

Peeling PH. Bayesian methods in music modelling. [Doctoral Dissertation]. University of Cambridge; 2011. Available from: https://www.repository.cam.ac.uk/handle/1810/237236 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.541860


University of Cambridge

19. Peeling, Paul. Bayesian methods in music modelling.

Degree: PhD, 2011, University of Cambridge

 This thesis presents several hierarchical generative Bayesian models of musical signals designed to improve the accuracy of existing multiple pitch detection systems and other musical… (more)

Subjects/Keywords: Music modelling; Signal processing; Bayesian methods

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

APA (6th Edition):

Peeling, P. (2011). Bayesian methods in music modelling. (Doctoral Dissertation). University of Cambridge. Retrieved from http://www.dspace.cam.ac.uk/handle/1810/237236https://www.repository.cam.ac.uk/bitstream/1810/237236/2/license.txt ; https://www.repository.cam.ac.uk/bitstream/1810/237236/5/thesis.pdf.txt ; https://www.repository.cam.ac.uk/bitstream/1810/237236/6/thesis.pdf.jpg

Chicago Manual of Style (16th Edition):

Peeling, Paul. “Bayesian methods in music modelling.” 2011. Doctoral Dissertation, University of Cambridge. Accessed January 19, 2020. http://www.dspace.cam.ac.uk/handle/1810/237236https://www.repository.cam.ac.uk/bitstream/1810/237236/2/license.txt ; https://www.repository.cam.ac.uk/bitstream/1810/237236/5/thesis.pdf.txt ; https://www.repository.cam.ac.uk/bitstream/1810/237236/6/thesis.pdf.jpg.

MLA Handbook (7th Edition):

Peeling, Paul. “Bayesian methods in music modelling.” 2011. Web. 19 Jan 2020.

Vancouver:

Peeling P. Bayesian methods in music modelling. [Internet] [Doctoral dissertation]. University of Cambridge; 2011. [cited 2020 Jan 19]. Available from: http://www.dspace.cam.ac.uk/handle/1810/237236https://www.repository.cam.ac.uk/bitstream/1810/237236/2/license.txt ; https://www.repository.cam.ac.uk/bitstream/1810/237236/5/thesis.pdf.txt ; https://www.repository.cam.ac.uk/bitstream/1810/237236/6/thesis.pdf.jpg.

Council of Science Editors:

Peeling P. Bayesian methods in music modelling. [Doctoral Dissertation]. University of Cambridge; 2011. Available from: http://www.dspace.cam.ac.uk/handle/1810/237236https://www.repository.cam.ac.uk/bitstream/1810/237236/2/license.txt ; https://www.repository.cam.ac.uk/bitstream/1810/237236/5/thesis.pdf.txt ; https://www.repository.cam.ac.uk/bitstream/1810/237236/6/thesis.pdf.jpg

20. Pajovic, Milutin. The development and application of random matrix theory in adaptive signal processing in the sample deficient regime.

Degree: 2014, MIT and Woods Hole Oceanographic Institution

 This thesis studies the problems associated with adaptive signal processing in the sample deficient regime using random matrix theory. The scenarios in which the sample… (more)

Subjects/Keywords: Matrix analytic methods; Adaptive signal processing

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APA (6th Edition):

Pajovic, M. (2014). The development and application of random matrix theory in adaptive signal processing in the sample deficient regime. (Thesis). MIT and Woods Hole Oceanographic Institution. Retrieved from http://hdl.handle.net/1912/6918

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):

Pajovic, Milutin. “The development and application of random matrix theory in adaptive signal processing in the sample deficient regime.” 2014. Thesis, MIT and Woods Hole Oceanographic Institution. Accessed January 19, 2020. http://hdl.handle.net/1912/6918.

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

MLA Handbook (7th Edition):

Pajovic, Milutin. “The development and application of random matrix theory in adaptive signal processing in the sample deficient regime.” 2014. Web. 19 Jan 2020.

Vancouver:

Pajovic M. The development and application of random matrix theory in adaptive signal processing in the sample deficient regime. [Internet] [Thesis]. MIT and Woods Hole Oceanographic Institution; 2014. [cited 2020 Jan 19]. Available from: http://hdl.handle.net/1912/6918.

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

Council of Science Editors:

Pajovic M. The development and application of random matrix theory in adaptive signal processing in the sample deficient regime. [Thesis]. MIT and Woods Hole Oceanographic Institution; 2014. Available from: http://hdl.handle.net/1912/6918

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


Rochester Institute of Technology

21. Kumar, Sriram. Learning Robust and Discriminative Manifold Representations for Pattern Recognition.

Degree: MS, Electrical Engineering, 2016, Rochester Institute of Technology

  Face and object recognition find applications in domains such as biometrics, surveillance and human computer interaction. An important component in any recognition pipeline is… (more)

Subjects/Keywords: Computer vision; Image processing; Machine learning; Pattern recognition; Statistical signal processing

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

APA (6th Edition):

Kumar, S. (2016). Learning Robust and Discriminative Manifold Representations for Pattern Recognition. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/8983

Chicago Manual of Style (16th Edition):

Kumar, Sriram. “Learning Robust and Discriminative Manifold Representations for Pattern Recognition.” 2016. Masters Thesis, Rochester Institute of Technology. Accessed January 19, 2020. https://scholarworks.rit.edu/theses/8983.

MLA Handbook (7th Edition):

Kumar, Sriram. “Learning Robust and Discriminative Manifold Representations for Pattern Recognition.” 2016. Web. 19 Jan 2020.

Vancouver:

Kumar S. Learning Robust and Discriminative Manifold Representations for Pattern Recognition. [Internet] [Masters thesis]. Rochester Institute of Technology; 2016. [cited 2020 Jan 19]. Available from: https://scholarworks.rit.edu/theses/8983.

Council of Science Editors:

Kumar S. Learning Robust and Discriminative Manifold Representations for Pattern Recognition. [Masters Thesis]. Rochester Institute of Technology; 2016. Available from: https://scholarworks.rit.edu/theses/8983

22. Sajadi, Nick. Time Reversal Compressive Sensing MIMO Radar Systems.

Degree: PhD, Computer Science, 2017, York University

 Active radar systems transmit a probing signal and use the return backscatters received from the channel to determine properties of the channel. After detecting the… (more)

Subjects/Keywords: Computer engineering; Time Reversal Signal Processing; Compressive Sensing; MIMO Radar Systems; Statistical Signal Processing

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

APA (6th Edition):

Sajadi, N. (2017). Time Reversal Compressive Sensing MIMO Radar Systems. (Doctoral Dissertation). York University. Retrieved from http://hdl.handle.net/10315/33518

Chicago Manual of Style (16th Edition):

Sajadi, Nick. “Time Reversal Compressive Sensing MIMO Radar Systems.” 2017. Doctoral Dissertation, York University. Accessed January 19, 2020. http://hdl.handle.net/10315/33518.

MLA Handbook (7th Edition):

Sajadi, Nick. “Time Reversal Compressive Sensing MIMO Radar Systems.” 2017. Web. 19 Jan 2020.

Vancouver:

Sajadi N. Time Reversal Compressive Sensing MIMO Radar Systems. [Internet] [Doctoral dissertation]. York University; 2017. [cited 2020 Jan 19]. Available from: http://hdl.handle.net/10315/33518.

Council of Science Editors:

Sajadi N. Time Reversal Compressive Sensing MIMO Radar Systems. [Doctoral Dissertation]. York University; 2017. Available from: http://hdl.handle.net/10315/33518


University of Adelaide

23. Dhu, Trevor. The use of fractal dimension for texture-based enhancement of aeromagnetic data.

Degree: 2008, University of Adelaide

 This thesis investigates the potential of fractal dimension (FD) as a tool for enhancing airborne magnetic data. More specifically, this thesis investigates the potential of… (more)

Subjects/Keywords: Fractal dimension; Aeromagnetic data image processing; Signal processing; Aeromagnetic prospecting.; Fractals  – Data processing.; Geology  – Statistical methods.; Geology  – Statistical methods  – Data processing.; Geophysics  – Statistical methods.; Geophysics  – Statistical method  – Data processing.

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

APA (6th Edition):

Dhu, T. (2008). The use of fractal dimension for texture-based enhancement of aeromagnetic data. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/49982

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):

Dhu, Trevor. “The use of fractal dimension for texture-based enhancement of aeromagnetic data.” 2008. Thesis, University of Adelaide. Accessed January 19, 2020. http://hdl.handle.net/2440/49982.

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

MLA Handbook (7th Edition):

Dhu, Trevor. “The use of fractal dimension for texture-based enhancement of aeromagnetic data.” 2008. Web. 19 Jan 2020.

Vancouver:

Dhu T. The use of fractal dimension for texture-based enhancement of aeromagnetic data. [Internet] [Thesis]. University of Adelaide; 2008. [cited 2020 Jan 19]. Available from: http://hdl.handle.net/2440/49982.

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

Council of Science Editors:

Dhu T. The use of fractal dimension for texture-based enhancement of aeromagnetic data. [Thesis]. University of Adelaide; 2008. Available from: http://hdl.handle.net/2440/49982

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


Michigan State University

24. Shan, Zeyong. Multichannel signal decomposition and separation in the time-frequency domain.

Degree: PhD, Electrical Engineering, 2009, Michigan State University

Subjects/Keywords: Signal processing – Statistical methods; Time-series analysis; Blind source separation; Frequency spectra

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

APA (6th Edition):

Shan, Z. (2009). Multichannel signal decomposition and separation in the time-frequency domain. (Doctoral Dissertation). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:17039

Chicago Manual of Style (16th Edition):

Shan, Zeyong. “Multichannel signal decomposition and separation in the time-frequency domain.” 2009. Doctoral Dissertation, Michigan State University. Accessed January 19, 2020. http://etd.lib.msu.edu/islandora/object/etd:17039.

MLA Handbook (7th Edition):

Shan, Zeyong. “Multichannel signal decomposition and separation in the time-frequency domain.” 2009. Web. 19 Jan 2020.

Vancouver:

Shan Z. Multichannel signal decomposition and separation in the time-frequency domain. [Internet] [Doctoral dissertation]. Michigan State University; 2009. [cited 2020 Jan 19]. Available from: http://etd.lib.msu.edu/islandora/object/etd:17039.

Council of Science Editors:

Shan Z. Multichannel signal decomposition and separation in the time-frequency domain. [Doctoral Dissertation]. Michigan State University; 2009. Available from: http://etd.lib.msu.edu/islandora/object/etd:17039


Hong Kong University of Science and Technology

25. Li, Jian. Statistical process control for multivariate categorical processes.

Degree: 2012, Hong Kong University of Science and Technology

 Whatever is the business, either manufacturing or service, quality is the most critical aspect, which affects the level of success of the business. The importance… (more)

Subjects/Keywords: Process control  – Statistical methods ; Multivariate analysis  – Data processing ; Quality control  – Statistical methods

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

APA (6th Edition):

Li, J. (2012). Statistical process control for multivariate categorical processes. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-7801 ; https://doi.org/10.14711/thesis-b1198695 ; http://repository.ust.hk/ir/bitstream/1783.1-7801/1/th_redirect.html

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):

Li, Jian. “Statistical process control for multivariate categorical processes.” 2012. Thesis, Hong Kong University of Science and Technology. Accessed January 19, 2020. http://repository.ust.hk/ir/Record/1783.1-7801 ; https://doi.org/10.14711/thesis-b1198695 ; http://repository.ust.hk/ir/bitstream/1783.1-7801/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Li, Jian. “Statistical process control for multivariate categorical processes.” 2012. Web. 19 Jan 2020.

Vancouver:

Li J. Statistical process control for multivariate categorical processes. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2012. [cited 2020 Jan 19]. Available from: http://repository.ust.hk/ir/Record/1783.1-7801 ; https://doi.org/10.14711/thesis-b1198695 ; http://repository.ust.hk/ir/bitstream/1783.1-7801/1/th_redirect.html.

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

Council of Science Editors:

Li J. Statistical process control for multivariate categorical processes. [Thesis]. Hong Kong University of Science and Technology; 2012. Available from: http://repository.ust.hk/ir/Record/1783.1-7801 ; https://doi.org/10.14711/thesis-b1198695 ; http://repository.ust.hk/ir/bitstream/1783.1-7801/1/th_redirect.html

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

26. Roshen, Jacob; Dr.Unnikrishnan, A. Development of Time - Frequency Techniques for Sonar Applications.

Degree: 2010, Cochin University of Science and Technology

 Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation.… (more)

Subjects/Keywords: Sonar Signal Processing; Digital Signal Processing; Time-Frequency Methods; Fractional Fourier Transform; Wigner Ville Distribution

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APA (6th Edition):

Roshen, Jacob; Dr.Unnikrishnan, A. (2010). Development of Time - Frequency Techniques for Sonar Applications. (Thesis). Cochin University of Science and Technology. Retrieved from http://dyuthi.cusat.ac.in/purl/2677

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):

Roshen, Jacob; Dr.Unnikrishnan, A. “Development of Time - Frequency Techniques for Sonar Applications.” 2010. Thesis, Cochin University of Science and Technology. Accessed January 19, 2020. http://dyuthi.cusat.ac.in/purl/2677.

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

MLA Handbook (7th Edition):

Roshen, Jacob; Dr.Unnikrishnan, A. “Development of Time - Frequency Techniques for Sonar Applications.” 2010. Web. 19 Jan 2020.

Vancouver:

Roshen, Jacob; Dr.Unnikrishnan A. Development of Time - Frequency Techniques for Sonar Applications. [Internet] [Thesis]. Cochin University of Science and Technology; 2010. [cited 2020 Jan 19]. Available from: http://dyuthi.cusat.ac.in/purl/2677.

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

Council of Science Editors:

Roshen, Jacob; Dr.Unnikrishnan A. Development of Time - Frequency Techniques for Sonar Applications. [Thesis]. Cochin University of Science and Technology; 2010. Available from: http://dyuthi.cusat.ac.in/purl/2677

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


UCLA

27. Dragomiretskiy, Konstantin. Variational Methods in Signal Decomposition and Image Processing.

Degree: Mathematics, 2015, UCLA

 The work presented in this dissertation is motivated by classical problems in signal and image processing from the perspective of variational and PDE-based methods. Analytically… (more)

Subjects/Keywords: Applied mathematics; Image Processing; Image Segmentation; Mode Decomposition; Signal Decomposition; Signal Processing; Variational Methods

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APA (6th Edition):

Dragomiretskiy, K. (2015). Variational Methods in Signal Decomposition and Image Processing. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/4zx6s9zs

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):

Dragomiretskiy, Konstantin. “Variational Methods in Signal Decomposition and Image Processing.” 2015. Thesis, UCLA. Accessed January 19, 2020. http://www.escholarship.org/uc/item/4zx6s9zs.

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

MLA Handbook (7th Edition):

Dragomiretskiy, Konstantin. “Variational Methods in Signal Decomposition and Image Processing.” 2015. Web. 19 Jan 2020.

Vancouver:

Dragomiretskiy K. Variational Methods in Signal Decomposition and Image Processing. [Internet] [Thesis]. UCLA; 2015. [cited 2020 Jan 19]. Available from: http://www.escholarship.org/uc/item/4zx6s9zs.

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

Council of Science Editors:

Dragomiretskiy K. Variational Methods in Signal Decomposition and Image Processing. [Thesis]. UCLA; 2015. Available from: http://www.escholarship.org/uc/item/4zx6s9zs

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


University of Southern California

28. Audhkhasi, Kartik. A computational framework for diversity in ensembles of humans and machine systems.

Degree: PhD, Electrical Engineering, 2014, University of Southern California

 My Ph.D. thesis presents a computational framework for diversity in ensembles or collections of humans and machine systems used for signal and information processing. Machine… (more)

Subjects/Keywords: signal processing; information processing; machine learning; ensemble methods; diversity

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

APA (6th Edition):

Audhkhasi, K. (2014). A computational framework for diversity in ensembles of humans and machine systems. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/445107/rec/144

Chicago Manual of Style (16th Edition):

Audhkhasi, Kartik. “A computational framework for diversity in ensembles of humans and machine systems.” 2014. Doctoral Dissertation, University of Southern California. Accessed January 19, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/445107/rec/144.

MLA Handbook (7th Edition):

Audhkhasi, Kartik. “A computational framework for diversity in ensembles of humans and machine systems.” 2014. Web. 19 Jan 2020.

Vancouver:

Audhkhasi K. A computational framework for diversity in ensembles of humans and machine systems. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2020 Jan 19]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/445107/rec/144.

Council of Science Editors:

Audhkhasi K. A computational framework for diversity in ensembles of humans and machine systems. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/445107/rec/144


Boston University

29. Aksoylar, Cem. Discovery of low-dimensional structure in high-dimensional inference problems.

Degree: PhD, Electrical & Computer Engineering, 2017, Boston University

 Many learning and inference problems involve high-dimensional data such as images, video or genomic data, which cannot be processed efficiently using conventional methods due to… (more)

Subjects/Keywords: Electrical engineering; Convex optimization; Learning on networks; Sparse recovery; Statistical complexity; Statistical signal processing

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

APA (6th Edition):

Aksoylar, C. (2017). Discovery of low-dimensional structure in high-dimensional inference problems. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/20836

Chicago Manual of Style (16th Edition):

Aksoylar, Cem. “Discovery of low-dimensional structure in high-dimensional inference problems.” 2017. Doctoral Dissertation, Boston University. Accessed January 19, 2020. http://hdl.handle.net/2144/20836.

MLA Handbook (7th Edition):

Aksoylar, Cem. “Discovery of low-dimensional structure in high-dimensional inference problems.” 2017. Web. 19 Jan 2020.

Vancouver:

Aksoylar C. Discovery of low-dimensional structure in high-dimensional inference problems. [Internet] [Doctoral dissertation]. Boston University; 2017. [cited 2020 Jan 19]. Available from: http://hdl.handle.net/2144/20836.

Council of Science Editors:

Aksoylar C. Discovery of low-dimensional structure in high-dimensional inference problems. [Doctoral Dissertation]. Boston University; 2017. Available from: http://hdl.handle.net/2144/20836


University of New Orleans

30. Tsiappoutas, Kyriakos Michael. Statistical Spectral Parameter Estimation of Acoustic Signals with Applications to Byzantine Music.

Degree: PhD, Physics, 2011, University of New Orleans

  Digitized acoustical signals of Byzantine music performed by Iakovos Nafpliotis are used to extract the fundamental frequency of each note of the diatonic scale.… (more)

Subjects/Keywords: statistical spectral estimation, fundamental frequency estimation, statistical signal processing, Fourier transform, autocorrelation, autoregression; Engineering Physics

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

APA (6th Edition):

Tsiappoutas, K. M. (2011). Statistical Spectral Parameter Estimation of Acoustic Signals with Applications to Byzantine Music. (Doctoral Dissertation). University of New Orleans. Retrieved from https://scholarworks.uno.edu/td/1358

Chicago Manual of Style (16th Edition):

Tsiappoutas, Kyriakos Michael. “Statistical Spectral Parameter Estimation of Acoustic Signals with Applications to Byzantine Music.” 2011. Doctoral Dissertation, University of New Orleans. Accessed January 19, 2020. https://scholarworks.uno.edu/td/1358.

MLA Handbook (7th Edition):

Tsiappoutas, Kyriakos Michael. “Statistical Spectral Parameter Estimation of Acoustic Signals with Applications to Byzantine Music.” 2011. Web. 19 Jan 2020.

Vancouver:

Tsiappoutas KM. Statistical Spectral Parameter Estimation of Acoustic Signals with Applications to Byzantine Music. [Internet] [Doctoral dissertation]. University of New Orleans; 2011. [cited 2020 Jan 19]. Available from: https://scholarworks.uno.edu/td/1358.

Council of Science Editors:

Tsiappoutas KM. Statistical Spectral Parameter Estimation of Acoustic Signals with Applications to Byzantine Music. [Doctoral Dissertation]. University of New Orleans; 2011. Available from: https://scholarworks.uno.edu/td/1358

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