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Evaluating And Improving The Efficiency Of Software And Algorithms For Sequence Data Analysis, Hugh L. Eaves
Evaluating And Improving The Efficiency Of Software And Algorithms For Sequence Data Analysis, Hugh L. Eaves
Theses and Dissertations
With the ever-growing size of sequence data sets, data processing and analysis are an increasingly large portion of the time and money spent on nucleic acid sequencing projects. Correspondingly, the performance of the software and algorithms used to perform that analysis has a direct effect on the time and expense involved. Although the analytical methods are widely varied, certain types of software and algorithms are applicable to a number of areas. Targeting improvements to these common elements has the potential for wide reaching rewards. This dissertation research consisted of several projects to characterize and improve upon the efficiency of several …
Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James
Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James
Theses and Dissertations
The purpose of the algorithm developed in this thesis was to create a post processing method that could resolve objects at low signal levels using polarization diversity and no knowledge of the atmospheric seeing conditions. The process uses a two-channel system, one unpolarized image and one linearly polarized image, in a GEM algorithm to reconstruct the object. Previous work done by Strong showed that a two-channel system using polarization diversity on short exposure imagery could produce images up to twice the diffraction limit. In this research, long exposure images were simulated and a simple Kolmogorov model used. This allowed for …
Range Estimation Algorithm Comparison In 3-D Flash Ladar Data, Steven P. Jordan
Range Estimation Algorithm Comparison In 3-D Flash Ladar Data, Steven P. Jordan
Theses and Dissertations
Range estimation algorithms have been applied to Laser Detection and Ranging (LADAR) data to test for accuracy and precision. Data was acquired from Matlab® simulations and an experiment using the Advanced Scientific Concepts 3-D flash LADAR camera. Simulated LADAR data was based on a Gaussian pulse shape model with Poisson noise added. Simulations were performed to test range estimation algorithm performance with respect to waveform position within the range gate. The effectiveness of each algorithm is presented in terms of its average root mean square error and standard deviation in 1000 trials. The measured data experiment examined the effectiveness of …
Type Ii Quantum Computing Algorithm For Computational Fluid Dynamics, James A. Scoville
Type Ii Quantum Computing Algorithm For Computational Fluid Dynamics, James A. Scoville
Theses and Dissertations
An algorithm is presented to simulate fluid dynamics on a three qubit type II quantum computer: a lattice of small quantum computers that communicate classical information. The algorithm presented is called a three qubit factorized quantum lattice gas algorithm. It is modeled after classical lattice gas algorithms which move virtual particles along an imaginary lattice and change the particles’ momentums using collision rules when they meet at a lattice node. Instead of moving particles, the quantum algorithm presented here moves probabilities, which interact via a unitary collision operator. Probabilities are determined using ensemble measurement and are moved with classical communications …
Multiframe Shift Estimation, Stephen A. Bruckart
Multiframe Shift Estimation, Stephen A. Bruckart
Theses and Dissertations
The purpose of this research was to develop a fundamental framework for a new approach to multiframe translational shift estimation in image processing. This thesis sought to create a new multiframe shift estimator, to theoretically prove and experimentally test key properties of it, and to quantify its performance according to several metrics. The new estimator was modeled successfully and was proven to be an unbiased estimator under certain common image noise conditions. Furthermore its performance was shown to be superior to the cross correlation shift estimator, a robust estimator widely used in similar image processing cases, according to several criteria. …
An Estimation Theory Approach To Detection And Ranging Of Obscured Targets In 3-D Ladar Data, Charles R. Burris
An Estimation Theory Approach To Detection And Ranging Of Obscured Targets In 3-D Ladar Data, Charles R. Burris
Theses and Dissertations
The purpose of this research is to develop an algorithm to detect obscured images in 3-D LADAR data. The real data used for this research was gathered using a FLASH LADAR system under development at AFRL/SNJM. The system transmits light with a wavelength of 1.55 micrometers and produces 20 128 X 128 temporally resolved images from the return pulse separated by less than 2 nanoseconds in time. New algorithms for estimating the range to a target in 3-D FLASH LADAR data were developed. Results from processing real data are presented and compared to the traditional correlation receiver for extracting ranges …
Pattern Search Ranking And Selection Algorithms For Mixed-Variable Optimization Of Stochastic Systems, Todd A. Sriver
Pattern Search Ranking And Selection Algorithms For Mixed-Variable Optimization Of Stochastic Systems, Todd A. Sriver
Theses and Dissertations
A new class of algorithms is introduced and analyzed for bound and linearly constrained optimization problems with stochastic objective functions and a mixture of design variable types. The generalized pattern search (GPS) class of algorithms is extended to a new problem setting in which objective function evaluations require sampling from a model of a stochastic system. The approach combines GPS with ranking and selection (R&S) statistical procedures to select new iterates. The derivative-free algorithms require only black-box simulation responses and are applicable over domains with mixed variables (continuous, discrete numeric, and discrete categorical) to include bound and linear constraints on …
Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra
Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra
Theses and Dissertations
The most recent research involved registering images in the presence of translations and rotations using one iteration of the redundant discrete wavelet transform. We extend this work by creating a new multiscale transform to register two images with translation or rotation differences, independent of scale differences between the images. Our two-dimensional multiscale transform uses an innovative combination of lowpass filtering and the continuous wavelet transform to mimic the two-dimensional redundant discrete wavelet transform. This allows us to obtain multiple subbands at various scales while maintaining the desirable properties of the redundant discrete wavelet transform. Whereas the discrete wavelet transform produces …
An Efficient Gps Position Determination Algorithm, Carlos R. Colon
An Efficient Gps Position Determination Algorithm, Carlos R. Colon
Theses and Dissertations
The use of detect, or closed-form solutions of the trilateration equations used to obtain the position fix in GPS receivers is investigated. The paper is concerned with the development of an efficient new position determination algorithm that uses the closed-form solution of the trilateration equations and works in the presence of pseudorange measurement noise and for an arbitrary number of satellites. in addition, an initial position guess is not required and good estimation performance is achieved even under high GDOP conditions. A two step GPS position determination algorithm which 1) entails the solution of a linear regression problem and, 2) …
Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson
Automatic Target Cueing Of Hyperspectral Image Data, Terry A. Wilson
Theses and Dissertations
Modern imaging sensors produce vast amounts data, overwhelming human analysts. One such sensor is the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor. The AVIRIS sensor simultaneously collects data in 224 spectral bands that range from 0.4µm to 2.5µm in approximately 10nm increments, producing 224 images, each representing a single spectral band. Autonomous systems are required that can fuse "important" spectral bands and then classify regions of interest if all of this data is to be exploited. This dissertation presents a comprehensive solution that consists of a new physiologically motivated fusion algorithm and a novel Bayes optimal self-architecting classifier …
Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki
Representations, Approximations, And Algorithms For Mathematical Speech Processing, Laura R. Suzuki
Theses and Dissertations
Representing speech signals such that specific characteristics of speech are included is essential in many Air Force and DoD signal processing applications. A mathematical construct called a frame is presented which captures the important time-varying characteristic of speech. Roughly speaking, frames generalize the idea of an orthogonal basis in a Hilbert space, Specific spaces applicable to speech are L2(R) and the Hardy spaces Hp(D) for p> 1 where D is the unit disk in the complex plane. Results are given for representations in the Hardy spaces involving Carleson's inequalities (and its extensions), …
New Algorithms For Moving-Bank Multiple Model Adaptive Estimation, Juan R. Vasquez
New Algorithms For Moving-Bank Multiple Model Adaptive Estimation, Juan R. Vasquez
Theses and Dissertations
The focus of this research is to provide methods for generating precise parameter estimates in the face of potentially significant parameter variations such as system component failures. The standard Multiple Model Adaptive Estimation (MMAE) algorithm uses a bank of Kalman filters, each based on a different model of the system. A new moving-bank MMAE algorithm is developed based on exploitation of the density data available from the MMAE. The methods used to exploit this information include various measures of the density data and a decision-making logic used to move, expand, and contract the MMAE bank of filters. Parameter discretization within …
Applications Of Unsupervised Clustering Algorithms To Aircraft Identification Using High Range Resolution Radar, Dzung Tri Pham
Applications Of Unsupervised Clustering Algorithms To Aircraft Identification Using High Range Resolution Radar, Dzung Tri Pham
Theses and Dissertations
Identification of aircraft from high range resolution (HRR) radar range profiles requires a database of information capturing the variability of the individual range profiles as a function of viewing aspect. This database can be a collection of individual signatures or a collection of average signatures distributed over the region of viewing aspect of interest. An efficient database is one which captures the intrinsic variability of the HRR signatures without either excessive redundancy typical of single-signature databases, or without the loss of information common when averaging arbitrary groups of signatures. The identification of 'natural' clustering of similar HRR signatures provides a …