Increased power quality problems due to intensive usage of power electronic devices resulted in development of software applications to perform quick harmonic analysis. However, the present harmonic analysis applications have special software or computer locks requirements and occupy huge memory and cost high. An application program (using Microsoft Visual C++) that is simple yet accurate in calculations; with no special software or high memory requirements is developed in this thesis work. The program uses the automatic acceptance criteria (AAC) and the harmonic penetration techniques in calculating the system voltages. Several userriendly features and tools that aid in better understanding of system harmonics are included in the program. Comparison of case study results with Superharm simulation results proves the program?s accuracy. This thesis work resulted in an informative and time saving program with which the user can document the study results and analyze them with minimum effort.

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No / Abstract: We develop a novel approach to estimate the n unknown constituent frequencies of a sinusoidal signal that comprises of unknown number, n, of sinusoids of unknown phases and unknown amplitudes. The approach has been applied to multiple sinusoidal signals in the presence of white Gaussian noise with varying signal to noise ratio (SNR). The approach is based on eigenspace analysis of Hankel matrix formed with the samples from averaged frequency spectrum of the signal obtained through multiple measurements. The eigenspace analysis is based on the newly developed 3M relationship which reflects and exploits the relationship between the consecutive sets of Maximum, Middle and Minimum eigenvalues of square symmetric matrix of the Hankel matrix. The 3M relationship exhibits a pattern in line with the order of the Hankel matrix and leads to parametric estimation of the constituent sinusoids. This paper also presents the relationship equation between the size of 3M relationship pattern and the dimensions of the Hankel matrix. The performance of the developed approach has been tested to correctly estimate multiple constituent frequencies within a noisy signal.

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Imagine your local creamery administers a survey asking their patrons to choose their five favorite ice cream flavors. Any data collected by this survey would be an example of partially ranked data, as the set of all possible flavors is only ranked into subsets of the chosen flavors and the non-chosen flavors. If the creamery asks you to help analyze this data, what approaches could you take? One approach is to use the natural symmetries of the underlying data space to decompose any data set into smaller parts that can be more easily understood. In this work, I describe how to use permutation representations of the symmetric group to create and study efficient algorithms that yield such decompositions.

In this Ph. D. thesis we discuss four different problems in analysis: (a) sharp inequalities related to the restriction phenomena for the Fourier transform, with emphasis on some Strichartz-type estimates; (b) extremal approximations of exponential type for the Gaussian and for a class of even functions, with applications to analytic number theory; (c) radial symmetrization approach to convolution-like inequalities for the Boltzmann collision operator; (d) regularity of maximal operators with respect to weak derivatives and weak continuity. / text