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Articles 1 - 7 of 7
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Application Of Optimization Techniques To Spectrally Modulated, Spectrally Encoded Waveform Design, Todd W. Beard
Application Of Optimization Techniques To Spectrally Modulated, Spectrally Encoded Waveform Design, Todd W. Beard
Theses and Dissertations
A design process is demonstrated for a coexistent scenario containing Spectrally Modulated, Spectrally Encoded (SMSE) and Direct Sequence Spread Spectrum (DSSS) signals. Coexistent SMSE-DSSS designs are addressed under both perfect and imperfect DSSS code tracking conditions using a non-coherent delay-lock loop (DLL). Under both conditions, the number of SMSE subcarriers and subcarrier spacing are the optimization variables of interest. For perfect DLL code tracking conditions, the GA and RSM optimization processes are considered independently with the objective function being end-to-end DSSS bit error rate. A hybrid GA-RSM optimization process is used under more realistic imperfect DLL code tracking conditions. In …
A Confidence Paradigm For Classification Systems, Nathan J. Leap
A Confidence Paradigm For Classification Systems, Nathan J. Leap
Theses and Dissertations
There is no universally accepted methodology to determine how much confidence one should have in a classifier output. This research proposes a framework to determine the level of confidence in an indication from a classifier system where the output is or can be transformed into a posterior probability estimate. This is a theoretical framework that attempts to unite the viewpoints of the classification system developer (or engineer) and the classification system user (or war-fighter). The paradigm is based on the assumptions that the system confidence acts like, or can be modeled as a value and that indication confidence can be …
Statistical Methods For Image Registration And Denoising, Matthew D. Sambora
Statistical Methods For Image Registration And Denoising, Matthew D. Sambora
Theses and Dissertations
This dissertation describes research into image processing techniques that enhance military operational and support activities. The research extends existing work on image registration by introducing a novel method that exploits local correlations to improve the performance of projection-based image registration algorithms. The dissertation also extends the bounds on image registration performance for both projection-based and full-frame image registration algorithms and extends the Barankin bound from the one-dimensional case to the problem of two-dimensional image registration. It is demonstrated that in some instances, the Cramer-Rao lower bound is an overly-optimistic predictor of image registration performance and that under some conditions, the …
Scramjet Fuel Injection Array Optimization Utilizing Mixed Variable Pattern Search With Kriging Surrogates, Bryan Sparkman
Scramjet Fuel Injection Array Optimization Utilizing Mixed Variable Pattern Search With Kriging Surrogates, Bryan Sparkman
Theses and Dissertations
Fuel-air mixing analysis of scramjet aircraft is often performed through ex- perimental research or Computational Fluid Dynamics (cfd) algorithms. Design optimization with these approaches is often impossible under a limited budget due to their high cost per run. This investigation uses jetpen, a known inexpensive analysis tool, to build upon a previous case study of scramjet design optimization. Mixed Variable Pattern Search (mvps) is compared to evolutionary algorithms in the optimization of two scramjet designs. The ¯rst revisits the previously stud- ied approach and compares the quality of mvps to prior results. The second applies mvps to a new scramjet …
Improving Mixed Variable Optimization Of Computational And Model Parameters Using Multiple Surrogate Functions, David Bethea
Improving Mixed Variable Optimization Of Computational And Model Parameters Using Multiple Surrogate Functions, David Bethea
Theses and Dissertations
This research focuses on reducing computational time in parameter optimization by using multiple surrogates and subprocess CPU times without compromising the quality of the results. This is motivated by applications that have objective functions with expensive computational times at high fidelity solutions. Applying, matching, and tuning optimization techniques at an algorithm level can reduce the time spent on unprofitable computations for parameter optimization. The objective is to recover known parameters of a flow property reference image by comparing to a template image that comes from a computational fluid dynamics simulation, followed by a numerical image registration and comparison process. Mixed …
Statistical Approach To The Characterization And Recognition Of Human Gaits, Derrick M. Chelliah
Statistical Approach To The Characterization And Recognition Of Human Gaits, Derrick M. Chelliah
Theses and Dissertations
This thesis addresses the final portion of a complete process for human gait recognition. The thesis takes as input information that has been generated from videotaping walking individuals and converting their gaits into numerical data that measures the locations of various points on the body through time. Beginning with this data, this thesis uses a variety of mathematical and statistical methods to create identifying signatures for each individual and identify them on the basis of that signature. The end goal is to achieve under controlled laboratory conditions human gait recognition, an identification method which does not require contact or cooperation …
Predicting Cost And Schedule Growth For Military And Civil Space Systems, Christina F. Rusnock
Predicting Cost And Schedule Growth For Military And Civil Space Systems, Christina F. Rusnock
Theses and Dissertations
Military and civil space acquisitions have received much criticism for their inability to produce realistic cost and schedule estimates. This research seeks to provide space systems cost estimators with a forecasting tool for space system cost and schedule growth by identifying factors contributing to growth, quantifying the relative impact of these factors, and establishing a set of models for predicting space system cost and schedule growth. The analysis considers data from both Department of Defense (DoD) and National Aeronautics and Space Administration (NASA) space programs. The DoD dataset includes 21 space programs that submitted developmental Selected Acquisition Reports between 1969 …