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You searched for +publisher:"Georgia Tech" +contributor:("Anderson, David"). Showing records 1 – 30 of 114 total matches.

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Georgia Tech

1. Lim, Juho. Faster than Nyquist signaling based on energy spreading transform and ideal energy spreading transform.

Degree: MS, Electrical and Computer Engineering, 2016, Georgia Tech

 The objective of this thesis is to develop a Faster than Nyquist Signaling (FTNS) scheme which is grounded on EST based Iterative Decision Feedback Equalization… (more)

Subjects/Keywords: Energy spreading transform; Faster than Nyquist signaling; FTN; FTNS; EST

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APA (6th Edition):

Lim, J. (2016). Faster than Nyquist signaling based on energy spreading transform and ideal energy spreading transform. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55533

Chicago Manual of Style (16th Edition):

Lim, Juho. “Faster than Nyquist signaling based on energy spreading transform and ideal energy spreading transform.” 2016. Masters Thesis, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/55533.

MLA Handbook (7th Edition):

Lim, Juho. “Faster than Nyquist signaling based on energy spreading transform and ideal energy spreading transform.” 2016. Web. 19 Oct 2019.

Vancouver:

Lim J. Faster than Nyquist signaling based on energy spreading transform and ideal energy spreading transform. [Internet] [Masters thesis]. Georgia Tech; 2016. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/55533.

Council of Science Editors:

Lim J. Faster than Nyquist signaling based on energy spreading transform and ideal energy spreading transform. [Masters Thesis]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55533


Georgia Tech

2. Balavoine, Aurèle. Implementation of the locally competitive algorithm on a field programmable analog array.

Degree: MS, Electrical and Computer Engineering, 2009, Georgia Tech

 Sparse approximation is an important class of optimization problem in signal and image processing applications. This thesis presents an analog solution to this problem, based… (more)

Subjects/Keywords: FPAA; Sparse approximation; LCA; Non-linear optimization; Hopfield neural networks; Signal processing; Neural networks (Computer science)

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APA (6th Edition):

Balavoine, A. (2009). Implementation of the locally competitive algorithm on a field programmable analog array. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/37255

Chicago Manual of Style (16th Edition):

Balavoine, Aurèle. “Implementation of the locally competitive algorithm on a field programmable analog array.” 2009. Masters Thesis, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/37255.

MLA Handbook (7th Edition):

Balavoine, Aurèle. “Implementation of the locally competitive algorithm on a field programmable analog array.” 2009. Web. 19 Oct 2019.

Vancouver:

Balavoine A. Implementation of the locally competitive algorithm on a field programmable analog array. [Internet] [Masters thesis]. Georgia Tech; 2009. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/37255.

Council of Science Editors:

Balavoine A. Implementation of the locally competitive algorithm on a field programmable analog array. [Masters Thesis]. Georgia Tech; 2009. Available from: http://hdl.handle.net/1853/37255


Georgia Tech

3. Wishon, Michael Joseph Doumit. Harnessing nonlinear dynamics for applications in high speed information processing.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 External-cavity lasers (ECLs) are characterized by nonlinear dynamics created when a laser is subjected to optical feedback from a distant reflector. ECLs were studied using… (more)

Subjects/Keywords: Nonlinear dynamics; Microwave photonics

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APA (6th Edition):

Wishon, M. J. D. (2018). Harnessing nonlinear dynamics for applications in high speed information processing. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60314

Chicago Manual of Style (16th Edition):

Wishon, Michael Joseph Doumit. “Harnessing nonlinear dynamics for applications in high speed information processing.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/60314.

MLA Handbook (7th Edition):

Wishon, Michael Joseph Doumit. “Harnessing nonlinear dynamics for applications in high speed information processing.” 2018. Web. 19 Oct 2019.

Vancouver:

Wishon MJD. Harnessing nonlinear dynamics for applications in high speed information processing. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/60314.

Council of Science Editors:

Wishon MJD. Harnessing nonlinear dynamics for applications in high speed information processing. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60314


Georgia Tech

4. Gong, Yunyi. Design of switch-less silicon-germanium bi-directional amplifier for loss compensation in passive transmit/receive modules.

Degree: MS, Electrical and Computer Engineering, 2018, Georgia Tech

 The objective of the proposed research is to investigate the design of switch-less bi-directional amplifier (BDA) for loss compensation in passive transmit/receive (T/R) modules, using… (more)

Subjects/Keywords: Bi-directional; Phased array; SiGe BiCMOS

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APA (6th Edition):

Gong, Y. (2018). Design of switch-less silicon-germanium bi-directional amplifier for loss compensation in passive transmit/receive modules. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61129

Chicago Manual of Style (16th Edition):

Gong, Yunyi. “Design of switch-less silicon-germanium bi-directional amplifier for loss compensation in passive transmit/receive modules.” 2018. Masters Thesis, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/61129.

MLA Handbook (7th Edition):

Gong, Yunyi. “Design of switch-less silicon-germanium bi-directional amplifier for loss compensation in passive transmit/receive modules.” 2018. Web. 19 Oct 2019.

Vancouver:

Gong Y. Design of switch-less silicon-germanium bi-directional amplifier for loss compensation in passive transmit/receive modules. [Internet] [Masters thesis]. Georgia Tech; 2018. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/61129.

Council of Science Editors:

Gong Y. Design of switch-less silicon-germanium bi-directional amplifier for loss compensation in passive transmit/receive modules. [Masters Thesis]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61129


Georgia Tech

5. Luo, Chenchi. Non-uniform sampling: algorithms and architectures.

Degree: PhD, Electrical and Computer Engineering, 2012, Georgia Tech

 Modern signal processing applications emerging in telecommunication and instrumentation industries have placed an increasing demand for ADCs with higher speed and resolution. The most fundamental… (more)

Subjects/Keywords: TIADC; Farrow structure; Compressive sensing; Sparsity; Analog-to-digital converters; Sampling (Statistics); Algorithms; Signal processing; Signal processing Digital techniques

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APA (6th Edition):

Luo, C. (2012). Non-uniform sampling: algorithms and architectures. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/45873

Chicago Manual of Style (16th Edition):

Luo, Chenchi. “Non-uniform sampling: algorithms and architectures.” 2012. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/45873.

MLA Handbook (7th Edition):

Luo, Chenchi. “Non-uniform sampling: algorithms and architectures.” 2012. Web. 19 Oct 2019.

Vancouver:

Luo C. Non-uniform sampling: algorithms and architectures. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/45873.

Council of Science Editors:

Luo C. Non-uniform sampling: algorithms and architectures. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/45873


Georgia Tech

6. Ramakrishnan, Shubha. A system design approach to neuromorphic classifiers.

Degree: PhD, Electrical and Computer Engineering, 2013, Georgia Tech

 This work considers alternative strategies to mainstream digital approaches to signal processing - namely analog and neuromorphic solutions, for increased computing efficiency. In the context… (more)

Subjects/Keywords: Analog signal processing; Machine learning; Bio-inspired; Signal processing; Neural networks (Computer science); Analog integrated circuits

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APA (6th Edition):

Ramakrishnan, S. (2013). A system design approach to neuromorphic classifiers. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/51718

Chicago Manual of Style (16th Edition):

Ramakrishnan, Shubha. “A system design approach to neuromorphic classifiers.” 2013. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/51718.

MLA Handbook (7th Edition):

Ramakrishnan, Shubha. “A system design approach to neuromorphic classifiers.” 2013. Web. 19 Oct 2019.

Vancouver:

Ramakrishnan S. A system design approach to neuromorphic classifiers. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/51718.

Council of Science Editors:

Ramakrishnan S. A system design approach to neuromorphic classifiers. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/51718


Georgia Tech

7. Shapero, Samuel Andre. Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions.

Degree: PhD, Electrical and Computer Engineering, 2013, Georgia Tech

 Sparse approximation is a Bayesian inference program with a wide number of signal processing applications, such as Compressed Sensing recovery used in medical imaging. Previous… (more)

Subjects/Keywords: Regularized least-squares; Sparse approximation; Analog circuits; FPAA; Neural network; Hopfield network; Locally competitive algorithm (LCA); Least squares; Bayesian statistical decision theory; Analog computers

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APA (6th Edition):

Shapero, S. A. (2013). Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/51719

Chicago Manual of Style (16th Edition):

Shapero, Samuel Andre. “Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions.” 2013. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/51719.

MLA Handbook (7th Edition):

Shapero, Samuel Andre. “Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions.” 2013. Web. 19 Oct 2019.

Vancouver:

Shapero SA. Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/51719.

Council of Science Editors:

Shapero SA. Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/51719


Georgia Tech

8. Raza, Syed H. Temporally consistent semantic segmentation in videos.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 The objective of this Thesis research is to develop algorithms for temporally consistent semantic segmentation in videos. Though many different forms of semantic segmentations exist,… (more)

Subjects/Keywords: Semantic segmentation; Temporal consistency; Causality; Videos; Occlusion boundaries; Depth estimation

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APA (6th Edition):

Raza, S. H. (2014). Temporally consistent semantic segmentation in videos. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53455

Chicago Manual of Style (16th Edition):

Raza, Syed H. “Temporally consistent semantic segmentation in videos.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/53455.

MLA Handbook (7th Edition):

Raza, Syed H. “Temporally consistent semantic segmentation in videos.” 2014. Web. 19 Oct 2019.

Vancouver:

Raza SH. Temporally consistent semantic segmentation in videos. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/53455.

Council of Science Editors:

Raza SH. Temporally consistent semantic segmentation in videos. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53455


Georgia Tech

9. Altaf, Muhammad Umair Bin. Environmental sounds: acquisition, analysis, and representation.

Degree: PhD, Electrical and Computer Engineering, 2015, Georgia Tech

 The dissertation presents the design and development of a systematic signal analysis and representation framework beyond short-time Fourier power spectrum for sounds, in particular environmental… (more)

Subjects/Keywords: Environmental sounds; Digital signal processing

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APA (6th Edition):

Altaf, M. U. B. (2015). Environmental sounds: acquisition, analysis, and representation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53953

Chicago Manual of Style (16th Edition):

Altaf, Muhammad Umair Bin. “Environmental sounds: acquisition, analysis, and representation.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/53953.

MLA Handbook (7th Edition):

Altaf, Muhammad Umair Bin. “Environmental sounds: acquisition, analysis, and representation.” 2015. Web. 19 Oct 2019.

Vancouver:

Altaf MUB. Environmental sounds: acquisition, analysis, and representation. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/53953.

Council of Science Editors:

Altaf MUB. Environmental sounds: acquisition, analysis, and representation. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53953


Georgia Tech

10. Kim, Ha Yang. Modeling and tracking time-varying clock drifts in wireless networks.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 Clock synchronization is one of fundamental requirements in distributed networks. However, the imperfection of crystal oscillators is a potential hurdle for network-wide collaboration and degrades… (more)

Subjects/Keywords: Clock synchronization; Clock drift; Measurement

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APA (6th Edition):

Kim, H. Y. (2014). Modeling and tracking time-varying clock drifts in wireless networks. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53988

Chicago Manual of Style (16th Edition):

Kim, Ha Yang. “Modeling and tracking time-varying clock drifts in wireless networks.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/53988.

MLA Handbook (7th Edition):

Kim, Ha Yang. “Modeling and tracking time-varying clock drifts in wireless networks.” 2014. Web. 19 Oct 2019.

Vancouver:

Kim HY. Modeling and tracking time-varying clock drifts in wireless networks. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/53988.

Council of Science Editors:

Kim HY. Modeling and tracking time-varying clock drifts in wireless networks. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53988


Georgia Tech

11. Bhatta, Debesh. Algorithms and methodology for incoherent undersampling based acquisition of high speed signal waveforms using low cost test instrumentation.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 The objective of this research is to develop and demonstrate low-complexity, robust, frequency-scalable, wide-band waveform acquisition techniques for testing high speed com- munication systems. High… (more)

Subjects/Keywords: Incoherent undersampling; Low cost testing; Waveform acquisition; High-speed testing

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APA (6th Edition):

Bhatta, D. (2014). Algorithms and methodology for incoherent undersampling based acquisition of high speed signal waveforms using low cost test instrumentation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54262

Chicago Manual of Style (16th Edition):

Bhatta, Debesh. “Algorithms and methodology for incoherent undersampling based acquisition of high speed signal waveforms using low cost test instrumentation.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/54262.

MLA Handbook (7th Edition):

Bhatta, Debesh. “Algorithms and methodology for incoherent undersampling based acquisition of high speed signal waveforms using low cost test instrumentation.” 2014. Web. 19 Oct 2019.

Vancouver:

Bhatta D. Algorithms and methodology for incoherent undersampling based acquisition of high speed signal waveforms using low cost test instrumentation. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/54262.

Council of Science Editors:

Bhatta D. Algorithms and methodology for incoherent undersampling based acquisition of high speed signal waveforms using low cost test instrumentation. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54262


Georgia Tech

12. Kim, Jonathan Chongkang. Classification of affect using novel voice and visual features.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 Emotion adds an important element to the discussion of how information is conveyed and processed by humans; indeed, it plays an important role in the… (more)

Subjects/Keywords: Speech signal processing; Machine learning; Classifier fusion; Multimodal analysis; Emotion; Affective computing; Human behavior analysis; Speech production

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APA (6th Edition):

Kim, J. C. (2014). Classification of affect using novel voice and visual features. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54301

Chicago Manual of Style (16th Edition):

Kim, Jonathan Chongkang. “Classification of affect using novel voice and visual features.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/54301.

MLA Handbook (7th Edition):

Kim, Jonathan Chongkang. “Classification of affect using novel voice and visual features.” 2014. Web. 19 Oct 2019.

Vancouver:

Kim JC. Classification of affect using novel voice and visual features. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/54301.

Council of Science Editors:

Kim JC. Classification of affect using novel voice and visual features. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54301


Georgia Tech

13. Cho, Mikyung. Analog predistortion for improvement of RF power amplifier efficiency and linearity.

Degree: PhD, Electrical and Computer Engineering, 2016, Georgia Tech

 The objective of this research is to implement analog systems that enable highly efficient and linear operations of the RF PAs used in wireless communication… (more)

Subjects/Keywords: RF; Power amplifier; Predistortion; Linearization

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APA (6th Edition):

Cho, M. (2016). Analog predistortion for improvement of RF power amplifier efficiency and linearity. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55648

Chicago Manual of Style (16th Edition):

Cho, Mikyung. “Analog predistortion for improvement of RF power amplifier efficiency and linearity.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/55648.

MLA Handbook (7th Edition):

Cho, Mikyung. “Analog predistortion for improvement of RF power amplifier efficiency and linearity.” 2016. Web. 19 Oct 2019.

Vancouver:

Cho M. Analog predistortion for improvement of RF power amplifier efficiency and linearity. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/55648.

Council of Science Editors:

Cho M. Analog predistortion for improvement of RF power amplifier efficiency and linearity. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55648


Georgia Tech

14. Temel, Dogancan. Understanding perceived quality through visual representations.

Degree: PhD, Electrical and Computer Engineering, 2016, Georgia Tech

 The formatting of images can be considered as an optimization problem, whose cost function is a quality assessment algorithm. There is a trade-off between bit… (more)

Subjects/Keywords: Perceived quality; Visual system; Contrast sensitivity; Suppression; Color perception; Color name; Color difference; Unsupervised learning; Spatial pooling; Boosting

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APA (6th Edition):

Temel, D. (2016). Understanding perceived quality through visual representations. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56289

Chicago Manual of Style (16th Edition):

Temel, Dogancan. “Understanding perceived quality through visual representations.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/56289.

MLA Handbook (7th Edition):

Temel, Dogancan. “Understanding perceived quality through visual representations.” 2016. Web. 19 Oct 2019.

Vancouver:

Temel D. Understanding perceived quality through visual representations. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/56289.

Council of Science Editors:

Temel D. Understanding perceived quality through visual representations. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56289


Georgia Tech

15. Lee, Jungwon. Efficient image compression system using a CMOS transform imager.

Degree: PhD, Electrical and Computer Engineering, 2009, Georgia Tech

 This research focuses on the implementation of the efficient image compression system among the many potential applications of a transform imager system. The study includes… (more)

Subjects/Keywords: Index reordering; Wavelet; CMOS imager; Vector quantization; Image compression; Metal oxide semiconductors, Complementary; Image compression; Algorithms

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APA (6th Edition):

Lee, J. (2009). Efficient image compression system using a CMOS transform imager. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/31825

Chicago Manual of Style (16th Edition):

Lee, Jungwon. “Efficient image compression system using a CMOS transform imager.” 2009. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/31825.

MLA Handbook (7th Edition):

Lee, Jungwon. “Efficient image compression system using a CMOS transform imager.” 2009. Web. 19 Oct 2019.

Vancouver:

Lee J. Efficient image compression system using a CMOS transform imager. [Internet] [Doctoral dissertation]. Georgia Tech; 2009. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/31825.

Council of Science Editors:

Lee J. Efficient image compression system using a CMOS transform imager. [Doctoral Dissertation]. Georgia Tech; 2009. Available from: http://hdl.handle.net/1853/31825


Georgia Tech

16. George, Jason. Harnessing resilience: biased voltage overscaling for probabilistic signal processing.

Degree: PhD, Electrical and Computer Engineering, 2011, Georgia Tech

 A central component of modern computing is the idea that computation requires determinism. Contrary to this belief, the primary contribution of this work shows that… (more)

Subjects/Keywords: Low power; Error prone; Probabilistic computing; Reduced-precision; Probabilistic CMOS; PCMOS; Biased voltage overscaling; BIVOS; Fixed-point arithmetic; Signal processing; Electric power consumption; Energy conservation

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APA (6th Edition):

George, J. (2011). Harnessing resilience: biased voltage overscaling for probabilistic signal processing. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/42812

Chicago Manual of Style (16th Edition):

George, Jason. “Harnessing resilience: biased voltage overscaling for probabilistic signal processing.” 2011. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/42812.

MLA Handbook (7th Edition):

George, Jason. “Harnessing resilience: biased voltage overscaling for probabilistic signal processing.” 2011. Web. 19 Oct 2019.

Vancouver:

George J. Harnessing resilience: biased voltage overscaling for probabilistic signal processing. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/42812.

Council of Science Editors:

George J. Harnessing resilience: biased voltage overscaling for probabilistic signal processing. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/42812


Georgia Tech

17. Garver, Paul W. MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters.

Degree: PhD, Electrical and Computer Engineering, 2017, Georgia Tech

 Extreme emitter density (EED) RF environments, defined as 10k-100k emitters within a footprint of less than 1 km squared, are becoming increasingly common with the… (more)

Subjects/Keywords: MAC layer; Localization; Data association; Time difference of arrival

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APA (6th Edition):

Garver, P. W. (2017). MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59224

Chicago Manual of Style (16th Edition):

Garver, Paul W. “MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters.” 2017. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/59224.

MLA Handbook (7th Edition):

Garver, Paul W. “MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters.” 2017. Web. 19 Oct 2019.

Vancouver:

Garver PW. MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/59224.

Council of Science Editors:

Garver PW. MAC layer assisted localization in wireless environments with multiple sensors and multiple emitters. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59224


Georgia Tech

18. Richard, Antoine. Automated analysis of overhead imagery for habitat segmentation.

Degree: MS, Electrical and Computer Engineering, 2018, Georgia Tech

 The overall objective of our project is to be able to classify the evolution of land usage since the advent of aerial imagery. In practice… (more)

Subjects/Keywords: Deep Learning; Neural Networks; Auto-encoders; habitat segmentation; Computer Vision; Machine Learning; land use detection

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APA (6th Edition):

Richard, A. (2018). Automated analysis of overhead imagery for habitat segmentation. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59291

Chicago Manual of Style (16th Edition):

Richard, Antoine. “Automated analysis of overhead imagery for habitat segmentation.” 2018. Masters Thesis, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/59291.

MLA Handbook (7th Edition):

Richard, Antoine. “Automated analysis of overhead imagery for habitat segmentation.” 2018. Web. 19 Oct 2019.

Vancouver:

Richard A. Automated analysis of overhead imagery for habitat segmentation. [Internet] [Masters thesis]. Georgia Tech; 2018. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/59291.

Council of Science Editors:

Richard A. Automated analysis of overhead imagery for habitat segmentation. [Masters Thesis]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59291


Georgia Tech

19. Nguyen, Van. Non-contact physiologically related motion sensing with ultra-wideband impulse radar.

Degree: PhD, Electrical and Computer Engineering, 2016, Georgia Tech

 Impulse Radio Ultra-wideband (IR-UWB) radar is a promising tool for non-contact, non-invasive sensing of physiological parameters, which could be valuable in identifying or preventing clinical… (more)

Subjects/Keywords: Non-contact; UWB radar; Heart rate estimation; Respiration rate estimation; Chest displacement estimation; Posture change detection; Vital signs monitoring

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APA (6th Edition):

Nguyen, V. (2016). Non-contact physiologically related motion sensing with ultra-wideband impulse radar. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59142

Chicago Manual of Style (16th Edition):

Nguyen, Van. “Non-contact physiologically related motion sensing with ultra-wideband impulse radar.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/59142.

MLA Handbook (7th Edition):

Nguyen, Van. “Non-contact physiologically related motion sensing with ultra-wideband impulse radar.” 2016. Web. 19 Oct 2019.

Vancouver:

Nguyen V. Non-contact physiologically related motion sensing with ultra-wideband impulse radar. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/59142.

Council of Science Editors:

Nguyen V. Non-contact physiologically related motion sensing with ultra-wideband impulse radar. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/59142


Georgia Tech

20. Fair, Kaitlin Lindsay. A biologically plausible sparse approximation solver on neuromorphic hardware.

Degree: PhD, Electrical and Computer Engineering, 2017, Georgia Tech

 We develop a novel design methodology to map the biologically plausible Locally Competitive Algorithm (LCA) to the brain-inspired TrueNorth chip to solve for the sparse… (more)

Subjects/Keywords: Neuromorphic; Bio-inspired; TrueNorth; Sparsity; Sparse approximation

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APA (6th Edition):

Fair, K. L. (2017). A biologically plausible sparse approximation solver on neuromorphic hardware. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59782

Chicago Manual of Style (16th Edition):

Fair, Kaitlin Lindsay. “A biologically plausible sparse approximation solver on neuromorphic hardware.” 2017. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/59782.

MLA Handbook (7th Edition):

Fair, Kaitlin Lindsay. “A biologically plausible sparse approximation solver on neuromorphic hardware.” 2017. Web. 19 Oct 2019.

Vancouver:

Fair KL. A biologically plausible sparse approximation solver on neuromorphic hardware. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/59782.

Council of Science Editors:

Fair KL. A biologically plausible sparse approximation solver on neuromorphic hardware. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59782


Georgia Tech

21. Ashouri, Hazar. Robust estimation of systolic time intervals using ballistocardiogram and seismocardiogram signals.

Degree: PhD, Electrical and Computer Engineering, 2017, Georgia Tech

 The objective of this dissertation is to Pave the way for non-invasive out-of-clinic monitoring of patients with heart failure using systolic time intervals (STIs) obtained… (more)

Subjects/Keywords: Seimocardiogram; Ballistocadiogram; Heart failure; Systolic time intervals

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APA (6th Edition):

Ashouri, H. (2017). Robust estimation of systolic time intervals using ballistocardiogram and seismocardiogram signals. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59819

Chicago Manual of Style (16th Edition):

Ashouri, Hazar. “Robust estimation of systolic time intervals using ballistocardiogram and seismocardiogram signals.” 2017. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/59819.

MLA Handbook (7th Edition):

Ashouri, Hazar. “Robust estimation of systolic time intervals using ballistocardiogram and seismocardiogram signals.” 2017. Web. 19 Oct 2019.

Vancouver:

Ashouri H. Robust estimation of systolic time intervals using ballistocardiogram and seismocardiogram signals. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/59819.

Council of Science Editors:

Ashouri H. Robust estimation of systolic time intervals using ballistocardiogram and seismocardiogram signals. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59819


Georgia Tech

22. Shafiq, Muhammad Amir. Computational seismic interpretation using attention models, texture dissimilarity, and learning.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 The exploration of oil and gas is a vital part of today's increasing power demands to meet the energy we need to power our homes,… (more)

Subjects/Keywords: Seismic interpretation; Automation; Gradient of texture; Visual saliency; Salsi; SeisSal; Unsupervised learning; Autoencoder; 3D FFT; Multispectral projections; Directional center-surround; Feature maps; Human visual system; Texture dissimilarity; F3 block; Netherlands; North Sea; SEAM; Great South Basin; New Zealand; Stratton; Listric faults; Texas Gulf Coast; Sparse classification

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APA (6th Edition):

Shafiq, M. A. (2018). Computational seismic interpretation using attention models, texture dissimilarity, and learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59889

Chicago Manual of Style (16th Edition):

Shafiq, Muhammad Amir. “Computational seismic interpretation using attention models, texture dissimilarity, and learning.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/59889.

MLA Handbook (7th Edition):

Shafiq, Muhammad Amir. “Computational seismic interpretation using attention models, texture dissimilarity, and learning.” 2018. Web. 19 Oct 2019.

Vancouver:

Shafiq MA. Computational seismic interpretation using attention models, texture dissimilarity, and learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/59889.

Council of Science Editors:

Shafiq MA. Computational seismic interpretation using attention models, texture dissimilarity, and learning. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59889


Georgia Tech

23. Whitaker, Bradley M. Modifying sparse coding to model imbalanced datasets.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 The objective of this research is to explore the use of sparse coding as a tool for unsupervised feature learning to more effectively model imbalanced… (more)

Subjects/Keywords: Sparse coding; Imbalanced data; Machine learning

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APA (6th Edition):

Whitaker, B. M. (2018). Modifying sparse coding to model imbalanced datasets. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59919

Chicago Manual of Style (16th Edition):

Whitaker, Bradley M. “Modifying sparse coding to model imbalanced datasets.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/59919.

MLA Handbook (7th Edition):

Whitaker, Bradley M. “Modifying sparse coding to model imbalanced datasets.” 2018. Web. 19 Oct 2019.

Vancouver:

Whitaker BM. Modifying sparse coding to model imbalanced datasets. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/59919.

Council of Science Editors:

Whitaker BM. Modifying sparse coding to model imbalanced datasets. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59919


Georgia Tech

24. Masood, Mir. Digitally-Assisted, Efficiency Enhanced, Linear RF Power Amplifier Architectures.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 This dissertation presents the use of advanced digital techniques in the development of efficiency enhanced, linearized power amplifier (PA) architectures. In this research, digital enhancements… (more)

Subjects/Keywords: pre-distortion; power amplifier; Doherty

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APA (6th Edition):

Masood, M. (2018). Digitally-Assisted, Efficiency Enhanced, Linear RF Power Amplifier Architectures. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61115

Chicago Manual of Style (16th Edition):

Masood, Mir. “Digitally-Assisted, Efficiency Enhanced, Linear RF Power Amplifier Architectures.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/61115.

MLA Handbook (7th Edition):

Masood, Mir. “Digitally-Assisted, Efficiency Enhanced, Linear RF Power Amplifier Architectures.” 2018. Web. 19 Oct 2019.

Vancouver:

Masood M. Digitally-Assisted, Efficiency Enhanced, Linear RF Power Amplifier Architectures. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/61115.

Council of Science Editors:

Masood M. Digitally-Assisted, Efficiency Enhanced, Linear RF Power Amplifier Architectures. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61115


Georgia Tech

25. Sahadat, Md Nazmus. Design and Evaluation of a multimodal Assistive Technology Using Tongue Commands, Head Movements, and Speech Recognition for People with Tetraplegia.

Degree: PhD, Electrical and Computer Engineering, 2019, Georgia Tech

 People with high level (C1-C4) spinal cord injury (SCI) cannot use their limbs to do the daily life activities by themselves without assistance. Current assistive… (more)

Subjects/Keywords: Assistive Technology Wheelchair Access Human-Computer Interaction Machine Learning Signal Processing Tongue Gesture Head Gesture Speech Recognition

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APA (6th Edition):

Sahadat, M. N. (2019). Design and Evaluation of a multimodal Assistive Technology Using Tongue Commands, Head Movements, and Speech Recognition for People with Tetraplegia. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61245

Chicago Manual of Style (16th Edition):

Sahadat, Md Nazmus. “Design and Evaluation of a multimodal Assistive Technology Using Tongue Commands, Head Movements, and Speech Recognition for People with Tetraplegia.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/61245.

MLA Handbook (7th Edition):

Sahadat, Md Nazmus. “Design and Evaluation of a multimodal Assistive Technology Using Tongue Commands, Head Movements, and Speech Recognition for People with Tetraplegia.” 2019. Web. 19 Oct 2019.

Vancouver:

Sahadat MN. Design and Evaluation of a multimodal Assistive Technology Using Tongue Commands, Head Movements, and Speech Recognition for People with Tetraplegia. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/61245.

Council of Science Editors:

Sahadat MN. Design and Evaluation of a multimodal Assistive Technology Using Tongue Commands, Head Movements, and Speech Recognition for People with Tetraplegia. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61245


Georgia Tech

26. Alshawi, Tariq. Uncertainty estimation of visual attention models using spatiotemporal analysis.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 In this dissertation, we analyze eye tracking data and video content to discover general patterns of human visual attention that can be used for estimating… (more)

Subjects/Keywords: Uncertainty; Saliency; Video processing

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APA (6th Edition):

Alshawi, T. (2018). Uncertainty estimation of visual attention models using spatiotemporal analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60217

Chicago Manual of Style (16th Edition):

Alshawi, Tariq. “Uncertainty estimation of visual attention models using spatiotemporal analysis.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/60217.

MLA Handbook (7th Edition):

Alshawi, Tariq. “Uncertainty estimation of visual attention models using spatiotemporal analysis.” 2018. Web. 19 Oct 2019.

Vancouver:

Alshawi T. Uncertainty estimation of visual attention models using spatiotemporal analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/60217.

Council of Science Editors:

Alshawi T. Uncertainty estimation of visual attention models using spatiotemporal analysis. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/60217


Georgia Tech

27. Odelowo, Babafemi. DEVELOPMENT OF A NEURAL NETWORK-BASED SPEECH ENHANCEMENT SYSTEM.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 Neural networks are powerful machine learning models that have, in the last few years, been applied to several audio and speech signal processing problems including… (more)

Subjects/Keywords: Speech enhancement; Noise reduction; Speech quality; Speech intelligibility; Extreme learning machines (ELM); Deep neural networks; Supervised learning; Post processing

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APA (6th Edition):

Odelowo, B. (2018). DEVELOPMENT OF A NEURAL NETWORK-BASED SPEECH ENHANCEMENT SYSTEM. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61617

Chicago Manual of Style (16th Edition):

Odelowo, Babafemi. “DEVELOPMENT OF A NEURAL NETWORK-BASED SPEECH ENHANCEMENT SYSTEM.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/61617.

MLA Handbook (7th Edition):

Odelowo, Babafemi. “DEVELOPMENT OF A NEURAL NETWORK-BASED SPEECH ENHANCEMENT SYSTEM.” 2018. Web. 19 Oct 2019.

Vancouver:

Odelowo B. DEVELOPMENT OF A NEURAL NETWORK-BASED SPEECH ENHANCEMENT SYSTEM. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/61617.

Council of Science Editors:

Odelowo B. DEVELOPMENT OF A NEURAL NETWORK-BASED SPEECH ENHANCEMENT SYSTEM. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61617


Georgia Tech

28. Hu, Yuting. Texture Representation and Analysis in Material Classification and Characterization.

Degree: PhD, Electrical and Computer Engineering, 2019, Georgia Tech

 Objects and scenes in the real world exhibit abundant textural information. Textures observed in the surfaces of natural objects are not only the appearance of… (more)

Subjects/Keywords: Texture representation; texture characterization; deep learning; texture classification; texture tracking; texture analysis; texture dataset; material recognition; material surface characterization

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APA (6th Edition):

Hu, Y. (2019). Texture Representation and Analysis in Material Classification and Characterization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61735

Chicago Manual of Style (16th Edition):

Hu, Yuting. “Texture Representation and Analysis in Material Classification and Characterization.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/61735.

MLA Handbook (7th Edition):

Hu, Yuting. “Texture Representation and Analysis in Material Classification and Characterization.” 2019. Web. 19 Oct 2019.

Vancouver:

Hu Y. Texture Representation and Analysis in Material Classification and Characterization. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/61735.

Council of Science Editors:

Hu Y. Texture Representation and Analysis in Material Classification and Characterization. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61735


Georgia Tech

29. Zhu, Lijun. Seismic processing via machine learning for event detection and phase picking.

Degree: PhD, Electrical and Computer Engineering, 2019, Georgia Tech

 A feasible solution for seismic event detection and phase picking is prototyped on an embedded system with seismic sensors using a lightweight convolutional neural network… (more)

Subjects/Keywords: Machine learning; Seismic; Phase picking; CNN

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APA (6th Edition):

Zhu, L. (2019). Seismic processing via machine learning for event detection and phase picking. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61770

Chicago Manual of Style (16th Edition):

Zhu, Lijun. “Seismic processing via machine learning for event detection and phase picking.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/61770.

MLA Handbook (7th Edition):

Zhu, Lijun. “Seismic processing via machine learning for event detection and phase picking.” 2019. Web. 19 Oct 2019.

Vancouver:

Zhu L. Seismic processing via machine learning for event detection and phase picking. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/61770.

Council of Science Editors:

Zhu L. Seismic processing via machine learning for event detection and phase picking. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61770


Georgia Tech

30. Sharma, Yachna. Surgical skill assessment using motion texture analysis.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 In this thesis, we propose a framework for automated assessment of surgical skills to expedite the manual assessment process and to provide unbiased evaluations with… (more)

Subjects/Keywords: Surgery; Skill; Classification; Prediction; Motion texture; Surgeons Rating of; Motion; Motor ability; Tactile sensors; Algorithms

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APA (6th Edition):

Sharma, Y. (2014). Surgical skill assessment using motion texture analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/51890

Chicago Manual of Style (16th Edition):

Sharma, Yachna. “Surgical skill assessment using motion texture analysis.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 19, 2019. http://hdl.handle.net/1853/51890.

MLA Handbook (7th Edition):

Sharma, Yachna. “Surgical skill assessment using motion texture analysis.” 2014. Web. 19 Oct 2019.

Vancouver:

Sharma Y. Surgical skill assessment using motion texture analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/1853/51890.

Council of Science Editors:

Sharma Y. Surgical skill assessment using motion texture analysis. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/51890

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