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You searched for +publisher:"University of Oklahoma" +contributor:("Antonio, John"). Showing records 1 – 8 of 8 total matches.

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University of Oklahoma

1. Chatterjee, Amlan. Parallel Algorithms for Counting Problems on Graphs Using Graphics Processing Units.

Degree: PhD, 2014, University of Oklahoma

 The availability of Graphics Processing Units (GPUs) with multicore architecture have enabled parallel computations using extensive multi-threading. Recent advancements in computer hardware have led to… (more)

Subjects/Keywords: GPU; CUDA; Graph Problems; Parallel Algorithms; Counting Problems

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APA (6th Edition):

Chatterjee, A. (2014). Parallel Algorithms for Counting Problems on Graphs Using Graphics Processing Units. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/13860

Chicago Manual of Style (16th Edition):

Chatterjee, Amlan. “Parallel Algorithms for Counting Problems on Graphs Using Graphics Processing Units.” 2014. Doctoral Dissertation, University of Oklahoma. Accessed January 22, 2021. http://hdl.handle.net/11244/13860.

MLA Handbook (7th Edition):

Chatterjee, Amlan. “Parallel Algorithms for Counting Problems on Graphs Using Graphics Processing Units.” 2014. Web. 22 Jan 2021.

Vancouver:

Chatterjee A. Parallel Algorithms for Counting Problems on Graphs Using Graphics Processing Units. [Internet] [Doctoral dissertation]. University of Oklahoma; 2014. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11244/13860.

Council of Science Editors:

Chatterjee A. Parallel Algorithms for Counting Problems on Graphs Using Graphics Processing Units. [Doctoral Dissertation]. University of Oklahoma; 2014. Available from: http://hdl.handle.net/11244/13860


University of Oklahoma

2. Suh, Joohee. The Context-Aware Learning Model.

Degree: PhD, 2017, University of Oklahoma

 The ultimate goal of this research is to build a novel, generalized, arbitrary-depth, neural controller that performs reward- and experience-based neuromodulatory learning, which is online,… (more)

Subjects/Keywords: Computer Science; Machine Learning; Artificial Intelligence; Robotics

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APA (6th Edition):

Suh, J. (2017). The Context-Aware Learning Model. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/51950

Chicago Manual of Style (16th Edition):

Suh, Joohee. “The Context-Aware Learning Model.” 2017. Doctoral Dissertation, University of Oklahoma. Accessed January 22, 2021. http://hdl.handle.net/11244/51950.

MLA Handbook (7th Edition):

Suh, Joohee. “The Context-Aware Learning Model.” 2017. Web. 22 Jan 2021.

Vancouver:

Suh J. The Context-Aware Learning Model. [Internet] [Doctoral dissertation]. University of Oklahoma; 2017. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11244/51950.

Council of Science Editors:

Suh J. The Context-Aware Learning Model. [Doctoral Dissertation]. University of Oklahoma; 2017. Available from: http://hdl.handle.net/11244/51950


University of Oklahoma

3. Hasan, Khondker. Prediction Models for Estimating the Efficiency of Distributed Multi-Core Systems.

Degree: PhD, 2014, University of Oklahoma

 The efficiency of a multi-core architecture is directly related to the mechanisms that map the threads (processes in execution) to the cores. Determining the resource… (more)

Subjects/Keywords: Computer Science

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APA (6th Edition):

Hasan, K. (2014). Prediction Models for Estimating the Efficiency of Distributed Multi-Core Systems. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/10454

Chicago Manual of Style (16th Edition):

Hasan, Khondker. “Prediction Models for Estimating the Efficiency of Distributed Multi-Core Systems.” 2014. Doctoral Dissertation, University of Oklahoma. Accessed January 22, 2021. http://hdl.handle.net/11244/10454.

MLA Handbook (7th Edition):

Hasan, Khondker. “Prediction Models for Estimating the Efficiency of Distributed Multi-Core Systems.” 2014. Web. 22 Jan 2021.

Vancouver:

Hasan K. Prediction Models for Estimating the Efficiency of Distributed Multi-Core Systems. [Internet] [Doctoral dissertation]. University of Oklahoma; 2014. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11244/10454.

Council of Science Editors:

Hasan K. Prediction Models for Estimating the Efficiency of Distributed Multi-Core Systems. [Doctoral Dissertation]. University of Oklahoma; 2014. Available from: http://hdl.handle.net/11244/10454


University of Oklahoma

4. Lucking, David. Digital-At-Every-Element Radar Resource Allocation for Multi-Target Tracking.

Degree: PhD, 2019, University of Oklahoma

 A sensor's performance is constrained by the amount of resources at its disposal and the utilization of those resources. A radar system, for example, has… (more)

Subjects/Keywords: Digital Arrays; Multi-Target Tracking; Radar Modeling; Radar Resource Management; Radar Signal Processing

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APA (6th Edition):

Lucking, D. (2019). Digital-At-Every-Element Radar Resource Allocation for Multi-Target Tracking. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/320358

Chicago Manual of Style (16th Edition):

Lucking, David. “Digital-At-Every-Element Radar Resource Allocation for Multi-Target Tracking.” 2019. Doctoral Dissertation, University of Oklahoma. Accessed January 22, 2021. http://hdl.handle.net/11244/320358.

MLA Handbook (7th Edition):

Lucking, David. “Digital-At-Every-Element Radar Resource Allocation for Multi-Target Tracking.” 2019. Web. 22 Jan 2021.

Vancouver:

Lucking D. Digital-At-Every-Element Radar Resource Allocation for Multi-Target Tracking. [Internet] [Doctoral dissertation]. University of Oklahoma; 2019. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11244/320358.

Council of Science Editors:

Lucking D. Digital-At-Every-Element Radar Resource Allocation for Multi-Target Tracking. [Doctoral Dissertation]. University of Oklahoma; 2019. Available from: http://hdl.handle.net/11244/320358


University of Oklahoma

5. Thompson, Daniel. Real-Time Narrowband and Wideband Beamforming Techniques for Fully-Digital RF Arrays.

Degree: PhD, 2017, University of Oklahoma

 Elemental digital beamforming offers increased flexibility for multi-function radio frequency (RF) systems supporting radar and communications applications. As fully digital arrays, components, and subsystems are… (more)

Subjects/Keywords: Real-Time; Elemental; Digital; Beamforming

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APA (6th Edition):

Thompson, D. (2017). Real-Time Narrowband and Wideband Beamforming Techniques for Fully-Digital RF Arrays. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/52942

Chicago Manual of Style (16th Edition):

Thompson, Daniel. “Real-Time Narrowband and Wideband Beamforming Techniques for Fully-Digital RF Arrays.” 2017. Doctoral Dissertation, University of Oklahoma. Accessed January 22, 2021. http://hdl.handle.net/11244/52942.

MLA Handbook (7th Edition):

Thompson, Daniel. “Real-Time Narrowband and Wideband Beamforming Techniques for Fully-Digital RF Arrays.” 2017. Web. 22 Jan 2021.

Vancouver:

Thompson D. Real-Time Narrowband and Wideband Beamforming Techniques for Fully-Digital RF Arrays. [Internet] [Doctoral dissertation]. University of Oklahoma; 2017. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11244/52942.

Council of Science Editors:

Thompson D. Real-Time Narrowband and Wideband Beamforming Techniques for Fully-Digital RF Arrays. [Doctoral Dissertation]. University of Oklahoma; 2017. Available from: http://hdl.handle.net/11244/52942


University of Oklahoma

6. Grounds, Nicolas. Feedback and Requirement Biasing for Enhancing Robustness of Scheduling Algorithms for Distributed System Processing.

Degree: PhD, 2018, University of Oklahoma

 Scheduling tasks in a distributed system (e.g., cloud computing) in order to optimize an objective such as minimizing deadline misses has been a topic of… (more)

Subjects/Keywords: scheduling; distributed processing; robustness

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APA (6th Edition):

Grounds, N. (2018). Feedback and Requirement Biasing for Enhancing Robustness of Scheduling Algorithms for Distributed System Processing. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/316298

Chicago Manual of Style (16th Edition):

Grounds, Nicolas. “Feedback and Requirement Biasing for Enhancing Robustness of Scheduling Algorithms for Distributed System Processing.” 2018. Doctoral Dissertation, University of Oklahoma. Accessed January 22, 2021. http://hdl.handle.net/11244/316298.

MLA Handbook (7th Edition):

Grounds, Nicolas. “Feedback and Requirement Biasing for Enhancing Robustness of Scheduling Algorithms for Distributed System Processing.” 2018. Web. 22 Jan 2021.

Vancouver:

Grounds N. Feedback and Requirement Biasing for Enhancing Robustness of Scheduling Algorithms for Distributed System Processing. [Internet] [Doctoral dissertation]. University of Oklahoma; 2018. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11244/316298.

Council of Science Editors:

Grounds N. Feedback and Requirement Biasing for Enhancing Robustness of Scheduling Algorithms for Distributed System Processing. [Doctoral Dissertation]. University of Oklahoma; 2018. Available from: http://hdl.handle.net/11244/316298


University of Oklahoma

7. Shah, Syed Naveed Hussain. NURTURING PROMOTES THE EVOLUTION OF LEARNING IN CHANGING ENVIRONMENTS.

Degree: PhD, 2015, University of Oklahoma

 An agent may interact with its environment and learn complex tasks based on evaluative feedback through a process known as reinforcement learning. Reinforcement learning requires… (more)

Subjects/Keywords: Machine Learning; Robotics; Artificial Intelligence; Reinforcement Learning; Evolutionary Computation; Genetic Algorithms; Nurturing Robotics; Evolution

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APA (6th Edition):

Shah, S. N. H. (2015). NURTURING PROMOTES THE EVOLUTION OF LEARNING IN CHANGING ENVIRONMENTS. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/15447

Chicago Manual of Style (16th Edition):

Shah, Syed Naveed Hussain. “NURTURING PROMOTES THE EVOLUTION OF LEARNING IN CHANGING ENVIRONMENTS.” 2015. Doctoral Dissertation, University of Oklahoma. Accessed January 22, 2021. http://hdl.handle.net/11244/15447.

MLA Handbook (7th Edition):

Shah, Syed Naveed Hussain. “NURTURING PROMOTES THE EVOLUTION OF LEARNING IN CHANGING ENVIRONMENTS.” 2015. Web. 22 Jan 2021.

Vancouver:

Shah SNH. NURTURING PROMOTES THE EVOLUTION OF LEARNING IN CHANGING ENVIRONMENTS. [Internet] [Doctoral dissertation]. University of Oklahoma; 2015. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11244/15447.

Council of Science Editors:

Shah SNH. NURTURING PROMOTES THE EVOLUTION OF LEARNING IN CHANGING ENVIRONMENTS. [Doctoral Dissertation]. University of Oklahoma; 2015. Available from: http://hdl.handle.net/11244/15447


University of Oklahoma

8. Li, Hongping. Fast and precise power prediction for combinatorial circuits considering glitching effects.

Degree: PhD, School of Computer Science, 2003, University of Oklahoma

 The power consumed by a combinational circuit is dictated by the switching activities of all signals associated with the circuit. Analytical approaches, named MCP and… (more)

Subjects/Keywords: Metal oxide semiconductors, Complementary.; Engineering, Electronics and Electrical.; Integrated circuits.; Computer Science.; Markov processes.

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APA (6th Edition):

Li, H. (2003). Fast and precise power prediction for combinatorial circuits considering glitching effects. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/666

Chicago Manual of Style (16th Edition):

Li, Hongping. “Fast and precise power prediction for combinatorial circuits considering glitching effects.” 2003. Doctoral Dissertation, University of Oklahoma. Accessed January 22, 2021. http://hdl.handle.net/11244/666.

MLA Handbook (7th Edition):

Li, Hongping. “Fast and precise power prediction for combinatorial circuits considering glitching effects.” 2003. Web. 22 Jan 2021.

Vancouver:

Li H. Fast and precise power prediction for combinatorial circuits considering glitching effects. [Internet] [Doctoral dissertation]. University of Oklahoma; 2003. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11244/666.

Council of Science Editors:

Li H. Fast and precise power prediction for combinatorial circuits considering glitching effects. [Doctoral Dissertation]. University of Oklahoma; 2003. Available from: http://hdl.handle.net/11244/666

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