Digital Commons Network^™

Dynamic Modeling Of Pwm And Single-Switch Single-Stage Power Factor Correction Converters, Guangyong Zhu

Retrospective Theses and Dissertations

The concept of averaging has been used extensively in the modeling of power electronic circuits to overcome their inherent time-variant nature. Among various methods, the PWM switch modeling approach is most widely accepted in the study of closed-loop stability and transient response because of its accuracy and simplicity. However, a non-ideal PWM switch model considering conduction losses is not available except for converters operating in continuous conduction mode (CCM) and under small ripple conditions. Modeling of conductor losses under large ripple conditions has not been reported in the open literature, especially when the converter operates in discontinuous conduction mode (DCM). …

Application Of The Fdtd Method For The Analysis Of Finite-Sized Phased Array Microstrip Antennas, Javier Gomez Tagle Rangel

Retrospective Theses and Dissertations

The Finite-Difference Time-Domain (FDTD) method has gained tremendous popularity in the past decade as a tool for solving Maxwell's equations. Phased Array Antennas find several applications including mobile communications ( cellular, personal communication systems and networks), satellite communications, global positioning system (GPS), aeronautical and radar systems. This dissertation describes the application of the FDTD method for calculating broadband characteristics of finite-sized phased array antennas consisting of microstrip elements fed with coaxial probes.

The characterization of such antennas is dependent upon the development of simulation tools that can accurately model general topologies including wires, dielectrics, conductors lumped elements and metallic strips. …

Constructive Induction Machines For Data Mining, Marek Perkowski, Stanislaw Grygiel, Qihong Chen, Dave Mattson

Electrical and Computer Engineering Faculty Publications and Presentations

"Learning Hardware" approach involves creating a computational network based on feedback from the environment (for instance, positive and negative examples from the trainer), and realizing this network in an array of Field Programmable Gate Arrays (FPGAs). Computational networks can be built based on incremental supervised learning (Neural Net training) or global construction (Decision Tree design). Here we advocate the approach to Learning Hardware based on Constructive Induction methods of Machine Learning (ML) using multivalued functions. This is contrasted with the Evolvable Hardware (EHW) approach in which learning/evolution is based on the genetic algorithm only. Various approaches to supervised inductive learning …

Feedback Control Theory For Dynamic Traffic Assignment, Pushkin Kachroo, Kaan Ozbay

Electrical & Computer Engineering Faculty Research

Traditionally, traffic assignment and traffic control in general have mostly been performed using optimisation techniques which do not lend themselves to real-time control. This volume presents feedback control techniques for performing traffic assignment in real-time, where traffic diversion control variables are instantaneous functions of sensed traffic variables. The authors outline the whole theory behind Intelligent Transportation Systems (ITS) which allows traffic variables to be sensed in real time and microprocessors to use the sensed traffic variable input to perform the traffic actuation tasks. They show h ow to design feedback controllers to perform dynamic traffic routing and assignment, and present …

Integrating Power Engineering Topics And Applications In Non-Power Courses, S. Legowski, Badrul H. Chowdhury, J. J. Cupal, R. G. Jacquot, B. J. W. Pierre, A. H. M. S. Ula, B. M. Wilamowski

Electrical and Computer Engineering Faculty Research & Creative Works

This paper investigates integrating power engineering material over the breadth of an electrical engineering curriculum. Electrical engineering curricula have a large number of required courses and many subareas for students to study. By introducing power concepts in a variety of courses, students may be motivated to take additional courses in the power area and are better prepared for the diverse background which will be required of them as practising power engineers. The important interrelationships between subareas of electrical engineering are better understood by students when cross discipline applications are discussed. This paper describes the introduction of power concepts and applications …

A Cloud-Removal Algorithm For Ssm/I Data, David G. Long, Douglas L. Daum, Quinn P. Remund

Faculty Publications

Microwave radiometers, while traditionally utilized in atmospheric and oceanic studies, can also be used in land surface applications. However, the problem of undesirable atmospheric effects caused by clouds and precipitation must be addressed. In this paper, temporal composite surface brightness images are generated from special sensor microwave/imager (SSM/I) data with the aid of new algorithms to eliminate small-scale distortion caused by clouds or precipitation. Mean, second-highest value, modified maximum average (MMA), and hybrid compositing algorithms are compared. The effectiveness of each algorithm is illustrated through simulation and real data distribution analysis. The results show that the second-highest value algorithm is …

Fed-Batch Dynamic Optimization Using Generalized Dual Heuristic Programming, Donald C. Wunsch, M. S. Iyer

Electrical and Computer Engineering Faculty Research & Creative Works

Traditionally fed-batch biochemical process optimization and control uses complicated theoretical off-line optimizers, with no online model adaptation or re-optimization. This study demonstrates the applicability, effectiveness, and economic potential of a simple phenomenological model for modeling, and an adaptive critic design, generalized dual heuristic programming, for online re-optimization and control of an aerobic fed-batch fermentor. The results are compared with those obtained using a heuristic random optimizer

Reduction Of Quantum Noise In Transmittance Estimation Using Photonecorrelated Beams, Majeed M. Hayat, Adel Joobeur, Bahaa E.A. Saleh

Electrical and Computer Engineering Faculty Research and Publications

The accuracy of optical measurements at low light levels is limited by the quantum noise of the source and by the random nature of the interaction with the measured object. The source noise may be reduced by use of nonclassical photon-number squeezed light. This paper considers the use of two photon-correlated beams (generated, for example, by spontaneous parametric downconversion) to measure the optical transmittance of an object. The photons of each beam obey a random Poisson process, but are synchronized in time. One beam is used to probe the object while the other is used as a reference providing information …

A Classification Of Techniques For The Compensation Of Time Delayed Processes. Part 1: Parameter Optimised Controllers, Aidan O'Dwyer, John Ringwood

Conference papers

An extensive literature exists on the compensation of time delayed processes. It is possible to identify themes that are common to many of the available techniques. The intention of the two parts of this paper is to provide a framework against which the literature may be viewed; Part 1 of the paper considers the use of parameter optimised controllers for the compensation problem, with Part 2 of the paper considering the use of structurally optimised compensators. Conclusions are drawn at the end of Part 2.

A Classification Of Techniques For The Compensation Of Time Delayed Processes. Part 2: Structurally Optimised Controllers, Aidan O'Dwyer, John Ringwood

Conference papers

Following on from Part 1, Part 2 of the paper considers the use of structurally optimised controllers to compensate time delayed processes.

Speaker Identification Using A Combination Of Different Parameters As Feature Inputs To An Artificial Neural Network Classifier, Viresh Moonasar, Ganesh K. Venayagamoorthy

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a technique using artificial neural networks (ANNs) for speaker identification that results in a better success rate compared to other techniques. The technique used in this paper uses both power spectral densities (PSDs) and linear prediction coefficients (LPCs) as feature inputs to a self organizing feature map to achieve a better identification performance. Results for speaker identification with different methods are presented and compared.

Application Of Composite Gyromagnetic Materials For Absorbing Radiation Produced By Microwave Oven, Marina Koledintseva, Alexander A. Kitaytsev, V. A. Konkin, V. P. Cheparin, Andrey A. Shinkov

Electrical and Computer Engineering Faculty Research & Creative Works

Composite gyromagnetic radioabsorbing material (RAM) on the basis of polycrystalline hexagonal ferrites is elaborated for the suppression of unwanted radiation produced by microwave ovens (MWO). Results of laboratory investigation of this material application in the MWO having a magnetron source of microwave radiation are represented.

Double-Talk Robust Fast Converging Algorithms For Network Echo Cancellation, T. Gansler, Steven L. Grant, J. Benesty, M. M. Sondhi

Electrical and Computer Engineering Faculty Research & Creative Works

Echo cancelers which cover longer impulse responses (greater than or equal to 64 ms) are desirable. Long responses create a need for more rapidly converging algorithms in order to meet the specifications for network echo cancelers devised by the ITU (International Telecommunication Union). In general, faster convergence implies a higher sensitivity to near-end disturbances, especially "double-talk". Recently, a fast converging algorithm called proportionate NLMS (normalized least mean squares) algorithm (PNLMS) has been proposed. This algorithm exploits the sparseness of the echo path. In this paper we propose a method for making the PNLMS algorithm more robust against double-talk. The slower …

Predictive Head Tracking For Virtual Reality, Donald C. Wunsch, Emad W. Saad, T. P. Caudell

Electrical and Computer Engineering Faculty Research & Creative Works

In virtual reality (VR), head movement is tracked through inertial and optical sensors. Computation and communication times result in delays between measurements and updating of the new frame in the head mounted display(HMD). These delays result in problems, including motion sickness. We use recurrent and time delay neural networks to predict the head location and use it to calculate the new frame. A predictability analysis is used in designing the prediction system

Dynamic Re-Optimization Of A Fed-Batch Fermentor Using Heuristic Dynamic Programming, Donald C. Wunsch, M. S. Iyer

Electrical and Computer Engineering Faculty Research & Creative Works

Traditionally, fed-batch biochemical process optimization and control uses complicated theoretical off-line optimizers, with no online model adaptation or re-optimization. This study demonstrates the applicability, effectiveness, and economic potential of a simple phenomenological model for modeling, and an adaptive critic design, heuristic dynamic programming, for online re-optimization and control of an aerobic fed-batch fermentor. The results are compared with those obtained using a heuristic random optimizer

A Distributed Algorithm For The Classification Of Images On A Network Of Workstations, S. R. Subramanya

Electrical and Computer Engineering Faculty Research & Creative Works

Image databases require content-based queries and retrievals. Fast and accurate retrievals for user queries depend on efficient indexing and searching schemes. The classification of images into different categories (classes) is an important task which facilitates the indexing and searching process. The classification of huge amounts of image data place enormous demands on computational requirements. Network of workstations (NOWs, also sometimes called clusters) are a cost-effective way of providing the much-needed computational power in such applications. This paper presents a distributed scheme for the classification of images in an image database, using a network of workstations. The results of the classification …

Extracting Consistent Weight Ratio Matrices From Inconsistent Judgement Matrices., Christian Alphonce

Tanzania Journal of Engineering and Technology (TJET)

The Analy,'ic Hierarchy Process (AHP) developed by Saaty Inore (han a decade ago has been widely applied in diverse decision making problenls ranging from socio-economic planning to engineering designs. One of the basic steps of this popular decision support tool is concerned with estimating a ratio scale of a set of entities from their inconsistent pairwise comparison judgement matrix. A number of estimation procedures for this purpose have been proposed. These include Saaty's eigenvector meihod, various geometric means methods, and methods using logarithmic least squares, least squares. and means Transformanons, amongst O,'hers. One Thing conunon to all these Inethods is …

What Can Humor And Advertising Teach Us About Legal Drafting?, Dallin D. Oaks, Jeremy Lewis

Faculty Publications

In his book Legal Drafting in a Nutshell, Haggard includes a useful chapter of nearly 50 pages in which he lists various lexical and structural elements and explains how these can lead to ambiguous writing. The kind of inventory approach that he presents is helpful and reveals that ambiguity doesn't just happen but often results from the careless use of identifiable structures or particular words.

Adaptive Channel Equalization Techniques, Saied Razavilar

Masters Theses

Inter Symbol Interference (ISI) is a characteristic of band-limited communication channels that can severely degrade the digital communication system performance if not treated properly. Channel equalization techniques may be used to mitigate the effects of ISI in the system, thereby improving the system capacity and performance. In this thesis, the problem of Inter Symbol Interference caused by the nonlinear characteristics of band limited communication channels and adaptive equalization techniques to combat the effects of ISI are discussed. First, the analysis of ISI in a band limited communication channel using a concrete theoretical framework is presented. Next, various adaptive equalization techniques …

An Image Model Based On Occluding Object Images And Maximum Entropy, John A. Stuller, Rahul Shah

Electrical and Computer Engineering Faculty Research & Creative Works

This Paper Introduces a Statistical Image Model based on Occlusion and Maximum Entropy. the Statistical Model Combines a Fundamental Property of Image Formation, Occlusion, with Both Object-Image Shape and Nonuniform Object-Image Intensity. the Model is a Composition of Individual Object-Images that Have Random Positions, Shapes, and Intensities, and that Occlude Both Background and One Another. We Derive the Autocorrelation and Second-Order Probability Density Functions of This Model and Give Several Examples. © 1998 IEEE.

A Recursive Green's Function Method For Boundary Integral Analysis Of Inhomogeneous Domains, Jim D. Freeze, Michael A. Jensen

Faculty Publications

The recursive Green's function method (RGFM) for computation of fields scattered by two-dimensional (2-D) inhomogeneous dielectric bodies is presented. The algorithm efficiently constructs the Green's function for the inhomogeneous region by recursively combining known Green's functions from smaller subdomains. The fields on the scatterer surface are then computed using a boundary integral formulation. Proper implementation of the RGFM results in computational and storage complexities which scale as N1.5 and N, respectively, where N is the total number of discrete cells in a domain. Comparisons of results obtained using the RGFM with those computed from moment method and exact solutions show …

Powergraf: An Educational Software Package For Power Systems Analysis And Design, Tian Yane, Max Darwin Anderson

Electrical and Computer Engineering Faculty Research & Creative Works

The purpose of PowerGraf is to present a graphical user interface (GUI) and a convenient tool for building one-line diagrams displaying data. The GUI is open and friendly for power systems design, analysis and control, because a picture provides a better illustration of cause-and-effect relationships than a tabular printout does. Basic elements such as buses, lines and transformers are given such that the power system topology is easily drawn with this tool, and the system parameters are entered on the picture and checked visually. This enables the power system topology and the system data to be shown on one picture …

The Latest World Wide Progress In Solid Oxide Fuel Cell, Yi Jiang

Journal of Electrochemistry

Solid oxide fuel cell (SOFC) is a novel, green electricity generation technology, which has been showing rapid development since 1980's. In light of its high efficiency, environmental friendly, fuel adaptability and long term stability, the Research, Development and Demonstration (RD&D) of this hype of full cell have been emphasized in a large number of developed countries. Based on the information communicated at the latest symposium on SOFC held last year in Aachen (Germany) and the knowledge gained through years of research in this field, a comprehensive review on the latest development of the tubular, this planar SOFC as well as …

Self-Enhancement Of Dynamic Gratings In Photogalvanic Crystals, Nickolai Kukhtarev, Sergei F. Lyuksyutov, Preben Buchhave, Tatiana Kukhtareva, K. Sayano, Partha P. Banerjee

Electrical and Computer Engineering Faculty Publications

We have developed a compact closed-form solution of the band transport model for high-contrast gratings in photogalvanic crystals. Our solution predicts the effect of the photoconductivity and the electric field grating enhancement due to the photogalvanic effect. We predict a pronounced dependence of the steady-state photogalvanic current on the contrast of the interference pattern and an increase of holographic storage time due to the enhancement of the photoconductivity grating contrast. In the high contrast limit and a large photogalvanic effect the refractive index grating will be shifted from the position of the intensity modulation pattern, contrary to the usually adopted …

A Virtual Classroom Via Dataconferencing: A Multi-Institutional Experience, Shelli K. Starrett, Anil Pahwa, Kraig J. Olejniczak, S. D. Sudhoff, Mariesa Crow

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents the experience of five faculty from four universities who are co-developing and team teaching courses using the world-wide web (WWW). In particular two novel power engineering courses, Flexible Control of Transmission Systems and Flexible Control of Distribuction Systems, introduce the student to the application of power electronic-based controllers, known specifically as flexible AC transmission systems (FACTS) controllers, to enhance the performance of the transmission and distribution systems in an electric power system. In order to leverage faculty expertise in the various topics included in each course, a unique partnership was formed among five faculty from the following …

Extension Of The Generalized Hebbian Algorithm For Principal Component Extraction, Fredric M. Ham, Inho Kim

Electrical Engineering and Computer Science Faculty Publications

Principal component analysis (PCA) plays an important role in various areas. In many applications it is necessary to adaptively compute the principal components of the input data. Over the past several years, there have been numerous neural network approaches to adaptively extract principal components for PCA. One of he most popular learning rules for training a single-layer linear network for principal component extraction is Sanger's generalized Hebbian algorithm (GHA). We have extended the GHA (EGHA) by including a positive-definite symmetric weighting matrix in the representation error-cost function that is used to derive the learning rule to train the network. The …

Validation Of Waimss Incident Duration Estimation Model, Wei Wu, Pushkin Kachroo, Kaan Ozbay

Electrical & Computer Engineering Faculty Research

This paper presents an effort to validate the traffic incident duration estimation model of WAIMSS (wide area incident management support system). Duration estimation model of WAIMSS predicts the incident duration based on an estimation tree which was calibrated using incident data collected in Northern Virginia. Due to the limited sample size, a full scale test of the distribution, mean and variance of incident duration was performed only for the root node of the estimation tree, white only mean tests were executed at all other nodes whenever a data subset was available. Further studies were also conducted on the model error …

Wide-Area Incident Management System On The Internet, Kaan Ozbay, Pushkin Kachroo

Electrical & Computer Engineering Faculty Research

The incident management process consists of four sequential steps-incident detection, response, clearance and recovery. Each of these components comprises of a number of operations and coordinated decision-making between the agencies involved. The provision of computer based support tools for the personnel involved will help develop appropriate strategies and increase efficiency and expediency. Existing systems are developed on various traditional computing platforms. However, with the advent of World Wide Web and Internet based programming tools such as Java, it is now possible to develop platform independent decision support tools for the incident management agencies. Any agency will be able to use …

Automatic Analysis Of Electronic Drawings Using Neural Network, Yi Shi

Dissertations

Neural network technique has been found to be a powerful tool in pattern recognition. It captures associations or discovers regularities with a set of patterns, where the types, number of variables or diversity of the data are very great, the relationships between variables are vaguely understood, or the relationships are difficult to describe adequately with conventional approaches.

In this dissertation, which is related to the research and the system design aiming at recognizing the digital gate symbols and characters in electronic drawings, we have proposed: (1) A modified Kohonen neural network with a shift-invariant capability in pattern recognition; (2) An …

Adaptive Bootstrap Signal Separators For Bpsk/Qam-Modulated Wireless Cdma Systems In A Multipath Environment, Nico J.M. Van Waes

Dissertations

CDMA is an attractive multiple-access scheme, because of its potential capacity increase and its anti-multipath fading capability. For satisfactory performance, however, the effect of the "near-far" problem has to be resolved. This problem can be combated by using power-control, which, however, results in an overall reduction in communication ranges, and thus in a loss of capacity. Among other methods for mitigating the near-far problem is the use of decorrelating receivers, both of fixed type, which directly utilizes the cross-correlation of the users codes, and of adaptive type, which uses recursive algorithms that leads to signal decorrelation. Not to lessen the …