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Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Theory and Algorithms

Air Force Institute of Technology

Pattern recognition systems

Publication Year

Articles 1 - 3 of 3

Full-Text Articles in Physical Sciences and Mathematics

Use Of Tabu Search In A Solver To Map Complex Networks Onto Emulab Testbeds, Jason E. Macdonald Mar 2007

Use Of Tabu Search In A Solver To Map Complex Networks Onto Emulab Testbeds, Jason E. Macdonald

Theses and Dissertations

The University of Utah's solver for the testbed mapping problem uses a simulated annealing metaheuristic algorithm to map a researcher's experimental network topology onto available testbed resources. This research uses tabu search to find near-optimal physical topology solutions to user experiments consisting of scale-free complex networks. While simulated annealing arrives at solutions almost exclusively by chance, tabu search incorporates the use of memory and other techniques to guide the search towards good solutions. Both search algorithms are compared to determine whether tabu search can produce equal or higher quality solutions than simulated annealing in a shorter amount of time. It …


Pattern Search Ranking And Selection Algorithms For Mixed-Variable Optimization Of Stochastic Systems, Todd A. Sriver Sep 2004

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 …


Weighted Mahalanobis Distance For Hyper-Ellipsoidal Clustering, Khaled S. Younis Dec 1996

Weighted Mahalanobis Distance For Hyper-Ellipsoidal Clustering, Khaled S. Younis

Theses and Dissertations

Cluster analysis is widely used in many applications, ranging from image and speech coding to pattern recognition. A new method that uses the weighted Mahalanobis distance (WMD) via the covariance matrix of the individual clusters as the basis for grouping is presented in this thesis. In this algorithm, the Mahalanobis distance is used as a measure of similarity between the samples in each cluster. This thesis discusses some difficulties associated with using the Mahalanobis distance in clustering. The proposed method provides solutions to these problems. The new algorithm is an approximation to the well-known expectation maximization (EM) procedure used to …