Thesis (M.S. in Electrical Engineering)--Vanderbilt University, Aug. 2007. / Title from title screen. Includes bibliographical references.

Thesis (M.S.)--Rochester Institute of Technology, 2007. / Typescript. Includes bibliographical references (leaves 98-100).

Thesis (M.S.)--Baylor University, 2006. / Includes bibliographical references (p. 48).

Thesis (M.S. in Engineering Acoustics)--Naval Postgraduate School, March 2007. / Thesis Advisor(s): Andrés Larraza, Bruce C. Denardo. "March 2007." Includes bibliographical references (p. 63-64). Also available in print.

Thesis (M.S.)--University of Delaware, 2008. / Principal faculty advisor: Dennis W. Prather, Dept. of Electrical & Computer Engineering. Includes bibliographical references.

Thesis (M.S.)--University of Texas at Dallas, 2008. / Includes vita. Includes bibliographical references (leaves 74-75)

Reductions in the cost and size of integrated circuits are allowing more and more complex functions to be included in previously simple tools such as lawn-mowers, ovens, and thermostats. Because of this, the process of synthesizing such functions from their initial representation to an optimal VLSI implementation is rarely hand-performed; instead, automated synthesis and optimization tools are a necessity. The factors such tools must take into account are numerous, including area (size), power consumption, and timing factors, to name just a few. Existing tools have traditionally focused upon optimization of two-level representations. However, new technologies such as Field Programmable Gate Arrays (FPGAs) have generated additional interest in three-level representations and structures such as Kronecker Decision Diagrams (KDDs). The reason for this is that when implementing a circuit on an FPGA, the cost of implementing exclusive-or logic is no more than that of traditional AND or OR gates. This dissertation investigates the use of the autocorrelation coefficients in logic synthesis for these types of structures; specifically, whether it is possible to pre-process a function to produce a subset of its autocorrelation coefficients and make use of this information in the choice of a three-level decomposition or of decomposition types within a KDD. This research began as a general investigation into the properties of autocorrelation coefficients of switching functions. Much work has centered around the use of a function's spectral coefficients in logic synthesis; however, very little work has used a function's autocorrelation coefficients. Their use has been investigated in the areas of testing, optimization for Programmable Logic Arrays (PLAs), identification of types of complexity measures, and in various DD-related applications, but in a limited manner. This has likely been due to the complexity in their computation. In order to investigate the uses of these coefficients, a fast computation technique was required, as well as knowledge of their basic properties. Both areas are detailed as part of this work, which demonstrates that it is feasible to quickly compute the autocorrelation coefficients. With these investigations as a foundation we further apply the autocorrelation coefficients to the development of a classification technique. The autocorrelation classes are similar to the spectral classes, but provide significantly different information. The dissertation demonstrates that some of this information highlighted by the autocorrelation classes may allow for the identification of exclusive-or logic within the function or classes of functions. In relation to this, a major contribution of this work involves the design and implementation of algorithms based on these results. The first of these algorithms is used to identify three-level decompositions for functions, and the second to determine decomposition type lists for KDD-representations. Each of these implementations compares well with existing tools, requiring on average less than one second to complete, and performing as well as the existing tools about 70% of the time. / Graduate

abstract: In software testing, components are tested individually to make sure each performs as expected. The next step is to confirm that two or more components are able to work together. This stage of testing is often difficult because there can be numerous configurations between just two components. Covering arrays are one way to ensure a set of tests will cover every possible configuration at least once. However, on systems with many settings, it is computationally intensive to run every possible test. Test prioritization methods can identify tests of greater importance. This concept of test prioritization can help determine which tests can be removed with minimal impact to the overall testing of the system. This thesis presents three algorithms that generate covering arrays that test the interaction of every two components at least twice. These algorithms extend the functionality of an established greedy test prioritization method to ensure important components are selected in earlier tests. The algorithms are tested on various inputs and the results reveal that on average, the resulting covering arrays are two-fifths to one-half times smaller than a covering array generated through brute force. / Dissertation/Thesis / Masters Thesis Computer Science 2015

abstract: Generalized Linear Models (GLMs) are widely used for modeling responses with non-normal error distributions. When the values of the covariates in such models are controllable, finding an optimal (or at least efficient) design could greatly facilitate the work of collecting and analyzing data. In fact, many theoretical results are obtained on a case-by-case basis, while in other situations, researchers also rely heavily on computational tools for design selection. Three topics are investigated in this dissertation with each one focusing on one type of GLMs. Topic I considers GLMs with factorial effects and one continuous covariate. Factors can have interactions among each other and there is no restriction on the possible values of the continuous covariate. The locally D-optimal design structures for such models are identified and results for obtaining smaller optimal designs using orthogonal arrays (OAs) are presented. Topic II considers GLMs with multiple covariates under the assumptions that all but one covariate are bounded within specified intervals and interaction effects among those bounded covariates may also exist. An explicit formula for D-optimal designs is derived and OA-based smaller D-optimal designs for models with one or two two-factor interactions are also constructed. Topic III considers multiple-covariate logistic models. All covariates are nonnegative and there is no interaction among them. Two types of D-optimal design structures are identified and their global D-optimality is proved using the celebrated equivalence theorem. / Dissertation/Thesis / Doctoral Dissertation Statistics 2018

Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2009 / This thesis presents the design, analysis and implementation of an eight-element phased array antenna for wideband X-band applications. The microstrip phased array antenna is designed using eight quasi-Yagi antennas in a linear configuration and is printed on RT/Duroid 6010LM substrate made by Rogers Corporation. The feeding network entails a uniform beamforming network as well as a non-uniform -25 dB Dolph-Tschebyscheff beamforming network, each with and without 45° delay lines, generating a squinted beam 14° from boresight. Antenna parameters such as gain, radiation patterns and impedance bandwidth (BW) are investigated in the single element as well as the array environment. Mutual coupling between the elements in the array is also predicted. The quasi-Yagi radiator employed as radiating element in the array measured an exceptional impedance bandwidth (BW) of 50% for a S11 < -10 dB from 6 GHz to 14 GHz, with 3 dB to 5 dB of absolute gain in the frequency range from 8 GHz to 11.5 GHz. The uniform broadside array measured an impedance BW of 20% over the frequency band and a gain between 9 dB to 11 dB, whereas the non-uniform broadside array measured a gain of 9 dB to 11 dB and an impedance BW of 14.5%. Radiation patterns are stable across the X-band. Beam scanning is illustrated in the E-plane for the uniform array as well as for the non-uniform array.