Electrical and Computer Engineering Commons^™

Adaptive Notch Filter For Single And Multiple Narrow-Band Interference, Selina Kuek Lin Mei

Theses : Honours

In this project, the adaptive notch filter for single and Multiple narrow-band interference is implemented using simplified LMS algorithm. Performances of the LMS adaptive algorithms is evaluated and analysed through simulation on the computer using Matlab. The algorithm are then written in C programme and implemented using Texas Instrument Tool which consist of TMS320C54x EMV board and Code Composer Studio.

Adaptive Notch Filter For Single And Multiple Narrow-Band Interference, Choy Chun Sin

Theses : Honours

In this project, the adaptive notch filter for single and Multiple narrow-band interference is implemented using simplified LMS algorithm. Performances of the LMS adaptive algorithms is evaluated and analysed through simulation on the computer using Matlab. The algorithm are then written in C programme and implemented using Texas Instrument Tool which consist of TMS320C54x EMV board and Code Composer Studio.

Multiresolution Gradient-Based Edge Detection In Noisy Images Using Wavelet Domain Filters, Yunwoo Lee, Samuel Peter Kozaitis

Electrical Engineering and Computer Science Faculty Publications

We detected edges in noisy images using multiresolution analysis with the wavelet transform. Products of wavelet coefficients at several scales were used to identify and locate edges. We found that it was important to consider the changes in edge position at different scales to detect edges in noisy imagery. We analyzed one-dimensional edges and compared the results of our approach with the first derivative of the signal. In addition, we compared the results of noisy images with another wavelet-based edge detection method. Our results led to improved edge detection in noisy images.

Fdtd Modeling Of Lumped Ferrites, Min Li, Xiao Luo, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

Implementing ferrites in finite-difference time-domain (FDTD) modeling requires special care because of the complex nature of the ferrite impedance. Considerable computational resources and time are required to directly implement a ferrite in the FDTD method. Fitting the ferrite impedance to an exponential series with the generalized-pencil-of-function (GPOF) method and using recursive convolution is an approach that minimizes the additional computational burden. An FDTD algorithm for a lumped ferrite using GPOF and recursive convolution is presented herein. Two different ferrite impedances in a test enclosure were studied experimentally to demonstrate the FDTD modeling approach. The agreement is generally good.

Integrated Floorplanning And Buffer Insertion For Bus-Based Microprocessor Designs, Faran Rafiq

Dissertations and Theses

In this thesis, we propose a novel algorithm for the interconnect driven floorplanning problem that integrates bus planning with floorplanning. This integrated floorplanner is intended for bus-based designs in which the layout is considered to be a set of blocks connected through buses. Each bus consists of a large number of wires. Our floorplanner allocates the exact location and shape of the interconnect (both above and between the circuit blocks) and ensures routability as well as optimizes the timing goals. Our experiments with benchmarks clearly show the superiority of integrated floorplanning approach over the classical floorplan-analyze-and-then-refloorplan approach. Our initial results …

Design And Evaluation Of A Specialized Computer Architecture For Manipulating Binary Decision Diagrams, Robert K. Hatt

Dissertations and Theses

Binary Decision Diagrams (BDDs) are an extremely important data structure used in many logic design, synthesis and verification applications. Symbolic problem representations make BDDs a feasible data structure for use on many problems that have discrete representations. Efficient implementations of BOD algorithms on general purpose computers has made manipulating large binary decision diagrams possible. Much research has gone into making BOD algorithms more efficient on general purpose computers. Despite amazing increases in performance and capacity of such computers over the last decade, they may not be the best way to solve large, specialized problems. A computer architecture designed specifically to …

A Blind Deconvolution Approach For Resolution Enhancement Of Near-Field Microwave Images, Ali Mohammad-Djafari, Nasser N. Qaddoumi, R. Zoughi

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper we propose a blind deconvolution method to enhance the resolution of images obtained by near-field microwave nondestructive techniques using an open ended rectangular waveguide probe. In fact, we model such images to be the result of a convolution of the real input images with a point spread function (PSF). This PSF depends mainly on the dimensions of the waveguide, the operating frequency, the nature of the object under test and standoff distance between the waveguide and the object. Unfortunately, it is very difficult to model this PSF from the physical data. For this reason, we consider the …

Comprehensive Analysis Of Edge Detection In Color Image Processing, Shu-Yu Zhu, Konstantinos N. Kostas Plataniotis, Anastasios N. Venetsanopoulos

Electrical Engineering and Computer Science Faculty Publications

Various approaches to edge detection for color images, including techniques extended from monochrome edge detection as well as vector space approaches, are examined. In particular, edge detection techniques based on vector order statistic operators and difference vector operators are studied in detail. Numerous edge detectors are obtained as special cases of these two classes of operators. The effect of distance measures on the performance of different color edge detectors is studied by employing distance measures other than the Euclidean norm. Variations are introduced to both the vector order statistic operators and the difference vector operators to improve noise performance. They …

Ultra-Wideband Tem Horns, Transient Arrays And Exponential Curves: A Fdtd Look, Troy S. Utton

Theses and Dissertations

This research investigates the possibility of applying exponentially curved conducting plates to single-element Transverse Electromagnetic (TEM) horns and their transient arrays to enhance the UWB characteristics already experienced by these radiators. The first part of this study demonstrates the Finite-Difference Time-Domain (FDTD) method's ability to duplicate experimental data, and establishes the baseline models used throughout the remainder of the research. The baseline models consist of the typical flat-triangle shaped conducting plates. The exponential taper models incorporate the exponential curves in the height, the width, and both the height and width directions. One, two- and four-element baseline configurations are compared to …

Nonlinear Constrained Optimizer And Parallel Processing For Golden Block Line Search, Duc T. Nguyen, Wilson H. Tang, Yeou K. Tung, Hakizumwami B. Runesha

Civil & Environmental Engineering Faculty Publications

Generalized exponential penalty functions are constructed for the multiplier methods in solving nonlinear programming problems. The non-smooth extreme constraint Gext is replaced by a single smooth constraint Gs by using the generalized exponential function (base a>1). The well-known K.S. function is found to be a special case of our proposed formulation. Parallel processing for Golden block line search algorithm is then summarized, which can also be integrated into our formulation. Both small and large-scale nonlinear programming problems (up to 2000 variables and 2000 nonlinear constraints) have been solved to validate the proposed algorithms.

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

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 H_p(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), …

Modified Multiple Model Adaptive Estimation (M3Ae) For Simultaneous Parameter And State Estimation, Mikel M. Miller

Theses and Dissertations

In many estimation problems, it is desired to estimate system states and parameters simultaneously. However, inherent to traditional estimation architectures of the past, the designer has had to make a trade-off decision between designs intended for accurate state estimation versus designs concerned with accurate parameter estimation. This research develops one solution to this trade-off decision by proposing a new architecture based on Kalman filtering (KF) and Multiple Model Adaptive Estimation (MMAE) techniques. This new architecture, the Modified-MMAE (M³AE), exploits the benefits of an MMAE designed for accurate parameter estimation, and yet performs at least as well in state …

Atmospheric Turbulence Scintillation Effects On Wavefront Tilt Estimation, James A. Louthain

Theses and Dissertations

A new atmospheric turbulence screen generator is developed for use in performance calculations of adaptive optics systems valid over a wide range of atmospheric turbulence parameters. The screen generator accounts for diffraction effects caused by weak turbulence and incorporates the phase, amplitude, and cross statistics of the perturbed optical field. The wavefront's phase and amplitude perturbations are taken from the correlation functions developed by Lee and Harp and the cross correlation of the phase and amplitude derived in this thesis. The screen generator uses a modal representation to perform a Fourier series expansion of the wavefront phase and amplitude over …

Atmospheric Induced Errors In Space-Time Adaptive Processing, Vinod D. Naga

Theses and Dissertations

This thesis examines the effects of atmospheric turbulence-induced phase perturbations on the performance of ground-based Space-Time Adaptive Processing (STAP) systems. Both Fully Adaptive Joint Domain Optimum and Partially Adaptive Factored-Time Space processing methods are examined. This thesis concentrates on the turbulence effects on STAP applied to ground-based arrays. This thesis further focuses on the capability of STAP to resolve targets at low elevation angles in the presence of turbulence. Only clutter interference and receiver noise are considered. Turbulence effects on the EM phase-front are calculated for turbulence strength Cn(2) values ranging from 5.0 x 10(exp -14) m-2/3 to 5.0 x …

A Wire Antenna Designed For Space Wave Radiation Over The Earth Using A Genetic Algorithm, Brian S. Sandlin

Theses and Dissertations

A wire antenna is designed for optimal performance at low elevation angles in the presence of a lossy half-space. A simple genetic algorithm (GA) and GENOCOP III software are each integrated with Numerical Electromagnetics Code Version 4.1 (NEC4.1) to optimize a wire antenna geometry for multiple objectives: power gain, azimuthal symmetry, and input impedance. The performance of the two versions of the integrated GA are compared. Several of the resulting antennas are analyzed, and an antenna is proposed for use in a Remote Intrusion Monitoring System (RIMS). Simulations suggest that the proposed antenna, which is well-matched, offers a significant increase …

Analytic Transfer Function Of The Forward Propagation Of Diffuse Photon Density Waves In Turbid Media With An Embedded Spherical Inhomogeneity, Deborah L. Lasocki

Theses and Dissertations

Diffusing photons can be used to detect and localize optical inhomogeneities embedded in turbid media such as clouds, fog, paint and human tissue. This thesis shows that a transfer function derived from an analytic solution of the Helmholtz equation can completely characterize in three dimensions the perturbations in the forward propagation phenomena caused by a spherical defect object in a multiple-scattering medium. Two models of the forward propagation behavior of diffuse photon density waves in homogeneous, infinite, turbid media that contains a spherical inhomogeneity are examined. The first model is an exact analytic solution based on a modal expansion in …

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 …

A Single Chip Low Power Implementation Of An Asynchronous Fft Algorithm For Space Applications, Bruce W. Hunt

Theses and Dissertations

A fully asynchronous fixed point FFT processor is introduced for low power space applications. The architecture is based on an algorithm developed by Suter and Stevens specifically for a low power implementation. The novelty of this architecture lies in its high localization of components and pipelining with no need to share a global memory. High throughput is attained using large numbers of small, local components working in parallel. A derivation of the algorithm from the discrete Fourier transform is presented followed by a discussion of circuit design parameters specifically, those relevant to space applications. The generic architecture is explained with …

Comparison Of Fdtd Algorithms For Subcellular Modeling Of Slots In Shielding Enclosures, Kuang-Ping Ma, Min Li, James L. Drewniak, Todd H. Hubing, Thomas Van Doren

Electrical and Computer Engineering Faculty Research & Creative Works

Subcellular modeling of thin slots in the finite-difference time-domain (FDTD) method is investigated. Two subcellular algorithms for modeling thin slots with the FDTD method are compared for application to shielding end osures in electromagnetic compatibility (EMC). The stability of the algorithms is investigated, and comparisons between the two methods for slots in planes, and slots in loaded cavities are made. Results for scattering from a finite-length slot in an infinite plane employing one of the algorithms are shown to agree well with published experimental results, and power delivered to an enclosure with a slot agree well with results measured for …

Training Strategies For Critic And Action Neural Networks In Dual Heuristic Programming Method, Christian Peter Paintz

Dissertations and Theses

This thesis discusses strategies for and details of training procedures for the Dual Heuristic Programming (DHP) methodology. This and other approximate dynamic programming approaches (HDP, DHP, GDHP) have been discussed in some detail in the literature, all being members of the Adaptive Critic Design (ACD) family. The example applications used here are the inverted pendulum problem and a fully nonlinear constant velocity bicycle steering model. The inverted pendulum has been successfully controlled using DHP, as reported in the literature. This thesis suggests and investigates several alternative D HP training procedures and compares their performance with respect to convergence speed and …

Comparison Of Three Clustering Algorithms And An Application To Color Image Compression, Jihun Cha, Laurene V. Fausett

Electrical Engineering and Computer Science Faculty Publications

This paper investigates a traditional clustering algorithm (K-means) and two neural networks (SOM and ART-F). The characteristics of each algorithm are illustrated by simulating geometric space data clustering. Then each algorithm is applied to image data sets to compress the size by reducing the number of colors from 256 to 16.

New Approaches To Column Compatibility Checking And Column-Based Input/Output Encoding For Curtis Decompositions Of Completely Or Incompletely Specified Switching Functions, Michael A. Burns

Dissertations and Theses

Cube calculus is an algebraic model used to process boolean functions. Cube calculus operations are widely used in logic optimization, logic synthesis, image processing and recognition, machine learning, and other applications which require massive logic operations.

The cube calculus operations can be carried out on general-purpose computers. Since these operations can involve several levels of nested loops, this approach has poor performance.

A cube calculus machine which has a special data path designed to speed up cube calculus operations is presented in this thesis. This c-qbe calculus machine can execute cube calculus operations 10 to 25 times faster than the …

Single-Layer Channel Routing And Placement With Single-Sided Nets, Ronald I. Greenberg, Jau-Der Shih

Computer Science: Faculty Publications and Other Works

This paper considers the optimal offset, feasible offset, and optimal placement problems for a more general form of single-layer VLSI channel routing than has usually been considered in the past. Most prior works require that every net has exactly one terminal on each side of the channel. As long as only one side of the channel contains multiple terminals of the same net, we provide linear-time solutions to all three problems. Such results are implausible if the placement of terminals is entirely unrestricted; in fact, the size of the output for the feasible offset problem may be Ω(n^2). The linear-time …

Variable Step Size Lms Adaptive Filters With Delayed Coefficient Updating, Guixian Xu

Electrical & Computer Engineering Theses & Dissertations

A new approach to delayed LMS adaptive filtering is presented, which uses a variable step size for coefficient updating to increase convergence speed and improve tracking characteristics. The new algorithm, called delayed variable step size LMS (DVLMS), is explained, analyzed, and simulated to experimentally determine performance characteristics. Three different strategies for adjusting the step size are examined, and their performance is compared. Also, simulation results are presented to show that the proposed DVLMS systems provide faster convergence and lower mis-adjustment than previously proposed DLMS systems.

Erp Analysis Using Matched Filtering And Wavelet Transform, Xueming Lin

Dissertations and Theses

Event related potentials (ERP's) carry very important information that relates to the performance of the brain functions of the human being. Further studies have identified that one component, in particular, P₃₀₀, is affected by the memory process. Matched filter is used to improved the SNR of signal ERP's. We use the output of the matched filter to distinguish the difference of the waveforms between normal subjects and memory-impaired subjects. In our study, we found that the peak values of the matched filtering output were different between normal subjects and memoryimpaired subjects. Also, as an application, wavelet transform is …

Adaptive Notch Filter, Yuchen Huang

Dissertations and Theses

The thesis presents a new adaptive notch filter (ANF) algorithm that is more accurate and efficient and has a faster convergent rate than previous ANF algorithms. In 1985, Nehorai designed an infinite impulse response (UR) ANF algorithm that has many advantages over previous ANF algorithms. It requires a minimal number of parameters with constrained poles and zeros. It has higher stability and sharper notches than any ANF algorithm until now. Because of the special filter structure and the recursive prediction error (RPE) method, however, the algorithm is very sensitive to the initial estimate of the filter coefficient and its covariance. …

An Algorithm For Automated Printed Circuit Board Layout And Routing Evaluation, Todd H. Hubing, Thomas Van Doren, James L. Drewniak, Puneet Grover, R. Lee Hill

Electrical and Computer Engineering Faculty Research & Creative Works

An algorithm has been developed to evaluate printed circuit boards that are designed using automated board layout and routing software. The algorithm analyzes aspects of component placement and trace routing while searching for violations of basic EMC design principles. The algorithm is implemented in code designed to work with a widely used board layout and routing program. This code can help novice and experienced circuit board designers to avoid mistakes that may result in serious electromagnetic compatibility problems.

Unified Bias Analysis Of Subspace-Based Doa Estimation Algorithms, Yang Lu

Dissertations and Theses

This thesis presents the unified bias analysis of subspace-based DOA estimation algorithms in terms of physical parameters such as source separation, signal coherence, number of senors and snapshots. The analysis reveals the direct relationship between the performance of the DOA algorithms and signal measurement conditions. Insights into different algorithms are provided. Based upon previous first-order subspace perturbations, second-order subspace perturbations are developed which provide basis for bias analysis and unification. Simulations verifying the theoretical bias analysis are presented.

Robust Linear Quadratic Regulation Using Neural Network, Kisuck Yoo, Michael Thursby

Electrical Engineering and Computer Science Faculty Publications

Using an Artificial Neural Network (ANN) trained with the Least Mean Square (LMS) algorithm we have designed a robust linear quadratic regulator for a range of plant uncertainty. Since there is a trade-off between performance and robustness in the conventional design techniques, we propose a design technique to provide the best mix of robustness and performance. Our approach is to provide different control strategies for different levels of uncertainty. We describe how to measure these uncertainties. We will compare our multiple strategies results with those of conventional techniques e.g. H∞ control theory. A Lyapunov equation is used to define stability …