Computer Sciences Commons^™

A Parallel Pipelined Computer Architecture For Digital Signal Processing, Haluk Gümüşkaya, Bülent Örenci̇k

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a parallel pipelined computer architecture and its six network configurations targeted for the implementation of a wide range of digital signal processing (DSP) algorithms described by both atomic and large grain data flow graphs. The proposed architecture is considered together with programmability, yielding a system solution that combines extensive concurrency with simple programming. It is an SSIMD (Skewed Single Instruction Multiple Data) or MIMD (Multiple Instruction Multiple Data) machine depending on the algorithms implemented and the programming methodologies. The concurrency that can be exploited by the algorithms using this Parallel pipelined architecture is both temporal and spatial …

Hierarchical Interconnection Network Architecture For Real-Time Systems, Bülent Örenci̇k

Turkish Journal of Electrical Engineering and Computer Sciences

A hierarchical network suitable for interconnection of real-time client processes in a distributed multiprocessor environment is presented in this paper. A multi-layer {\it Communication Unit} (CU) prototype is developed for this purpose. This unit offers the client processes communication services for real-time operation. These services are structured in such a way that they do not depend on the characteristics of the communication medium. The basic hardware of the CU consists of a PC compatible card connected to the VME Bus. Client processes run on target cards (Motorola MVME-162) which are attached to the same bus. Target cards together with a …

State Of Art In Realistic Head Modeling For Electro-Magnetic Source Imaging Of The Human Brain, Nevzat G. Gençer, İ. Oğuz Tanzer, M. Kemal Özdemi̇r, Can E. Acar, Mert Sungur

Turkish Journal of Electrical Engineering and Computer Sciences

Electric currents produced by the neural activity in the brain create electric potentials on the scalp and magnetic field distribution outside the scalp. Measuring electric and magnetic fields provides a means to understand the spatio-temporal distribution of the neural activity. The representations of the intracellular electric current of active cell populations based on bimodal data are called electro-magnetic source image (EMSI). With the recent development of large arrays of magnetic sensors, and systems for measuring scalp voltages at more than 100 locations, it is now feasible to implement computational methods that employ numerical models which incorporate the correct geometry and …

Imaging Tissue Conductivity Via Contactless Measurements: A Feasibility Study, Nevzat G. Gençer, M. Nejat Tek

Turkish Journal of Electrical Engineering and Computer Sciences

The feasibility of a new imaging system is investigated. This system will be used to image electrical conductivity distribution of biological tissues via contactless measurements. This will be achieved by introducing currents in the conductive medium using time-varying magnetic fields and measuring the magnetic fields of the induced currents. Consequently, the imaging system consists of transmitter and receiver coils placed nearby the conductive body. In this study, the basic features of the coplanar and coaxial coils are studied. The validity of the simplifying assumptions for the governing field equations is investigated. It is found that, for operating frequency of 100 …

Imaging Electrical Current Density Using Nuclear Magnetic Resonance, B. Murat Eyüpoğlu, Ravinder Reddy, John S. Leigh

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, images of nonuniform and uniform electric current density in conductor phantoms, which contain magnetic resonance active nuclei, are produced using Magnetic Resonance Imaging (MRI). A standard spin echo pulse sequence is used, with the addition of a bipolar current pulse. The flux density parallel to the main magnetic field, generated by the current pulse, is encoded in the phase of the complex MR image. The spatial distribution of magnetic flux density is extracted from the phase image. Current density is calculated using the magnetic flux density. This fairly recent technique is known as Magnetic Resonance Current Density …

Use Of The Magnetic Field Generated By The Internal Distribution Of Injected Currents For Electrical Impedance Tomography (Mr-Eit), Y. Zi̇ya İder, Özlem Bi̇rgül

Turkish Journal of Electrical Engineering and Computer Sciences

In two dimensional conventional Electrical Impedance Tomography (EIT), volume conductor is probed by means of injected currents, and peripheral voltage measurements are used as input to the reconstruction algorithm. The current that flows in the 2D object creates magnetic fields that are perpendicular to the plane of imaging. Such magnetic fields can be measured using magnetic resonance tomography. In this study, use of this magnetic field generated by the injected currents, for the purpose of reconstructing the conductivity distribution, is studied. Sensitivity matrix relating the magnetic field to the element conductivities is calculated using the Finite Element Method and Biot-Savart …

Fdtd Evaluation Of The Sar Distribution In A Human Head Near A Mobile Cellular Phone, Selçuk Paker, Levent Sevgi̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, Finite-Difference Time-Domain (FDTD) method is used to calculate the Specific Absorbtion Rate (SAR; defined as the power absorbed by unit mass of the tissue) distribution in a human head near a hand-held cellular phone. A three dimensional FDTD algorithm is built in cartesian coordinates. A discrete human head model, derived from a Nuclear Magnetic Resonance (NMR) image by semi-automatic algorithm, is located within FDTD volume together with a discrete hand-held receiver model. FDTD simulations are carried out for both european GSM (operating at 900MHz) and DECT (operating at 1.8GHz) systems with a quarter-wavelength antenna, mounted on top …

Cardiac Passive Acoustic Localization: Cardiopal, Yildirim Bahadirlar, Hali̇l Özcan Gülçür

Turkish Journal of Electrical Engineering and Computer Sciences

A novel non-invasive system is proposed as an adjunct diagnostic tool for cardiac disorders, which is based on processing of the heart sounds acquired using a specially designed 2-D passive acoustic array. In addition to the acoustic array, the system consists of a personal computer, specially developed instrumentation and interface hardware and an adaptive array processing scheme. A signal model is constructed in accordance with the basic assumptions made for very near-field low frequency sources. The multiple signal characterization (MUSIC) method together with the model is used for the localization of assumed point sources in the heart. Locations of the …

Visualization And Animation Of A Missile/Target Encounter, Jeffrey T. Bush

Theses and Dissertations

Existing missile/target encounter modeling and simulation systems focus on improving probability of kill models. Little research has been done to visualize these encounters. These systems can be made more useful to the engineers by incorporating current computer graphics technology for visualizing and animating the encounter. Our research has been to develop a graphical simulation package for visualizing both endgame and full fly-out encounters. Endgame visualization includes showing the interaction of a missile, its fuze cone proximity sensors, and its target during the final fraction of a second of the missile/target encounter. Additionally, this system displays dynamic effects such as the …

Breast Cancer Mass Detection Using Difference Of Gaussians And Pulse Coupled Neural Networks, Donald A. Cournoyer

Theses and Dissertations

CAD, serving as a second reader, has been shown to improve the success of radiologists at detecting breast cancer. This thesis will develop a new algorithm to identify masses in mammograms. The system developed for this thesis will be capable of assisting a radiologist in making decisions.

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 …

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 …

Simulation Study Of Learning Automata Games In Automated Highway Systems, Cem Unsal, Pushkin Kachroo, John S. Bay

Electrical & Computer Engineering Faculty Research

One of the most important issues in Automated Highway System (AHS) deployment is intelligent vehicle control. While the technology to safely maneuver vehicles exists, the problem of making intelligent decisions to improve a single vehicle’s travel time and safety while optimizing the overall traffic flow is still a stumbling block. We propose an artificial intelligence technique called stochastic learning automata to design an intelligent vehicle path controller. Using the information obtained by on-board sensors and local communication modules, two automata are capable of learning the best possible (lateral and longitudinal) actions to avoid collisions. This learning method is capable of …

Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay

Electrical & Computer Engineering Faculty Research

A new method for performing dynamic traffic assignment (DTA) is presented which is applicable in real time, since the solution is based on feedback control. This method employs the design of nonlinear H∞ feedback control systems which is robust to certain class of uncertainties in the system. The solution aims at achieving user equilibrium on alternate routes in a network setting.

Investigating The Use Of Kalman Filtering Approaches For Dynamic Origin-Destination Trip Table Estimation, Pushkin Kachroo, Kaan Ozbay, Arvind Narayanan

Electrical & Computer Engineering Faculty Research

This paper studies the applicability of Kalman filtering approaches for network wide traveler origin-destination estimation from link traffic volumes. The paper evaluates the modeling assumptions of the Kalman filters and examines the implications of such assumptions.

Minimizing Channel Density With Movable Terminals, Ronald I. Greenberg, Jau-Der Shih

Computer Science: Faculty Publications and Other Works

We give algorithms to minimize density for VLSI channel routing problems with terminals that are movable subject to certain constraints. The main cases considered are channels with linear order constraints, channels with linear order constraints and separation constraints, channels with movable modules containing fixed terminals, and channels with movable modules and terminals. In each case, we improve previous results for running time and space by a factor of L/\lgn and L, respectively, where L is the channel length, and n is the number of terminals.

Parallel Algorithms For Single-Layer Channel Routing, Ronald I. Greenberg, Shih-Chuan Hung, Jau-Der Shih

Computer Science: Faculty Publications and Other Works

We provide efficient parallel algorithms for the minimum separation, offset range, and optimal offset problems for single-layer channel routing. We consider all the variations of these problems that are known to have linear- time sequential solutions rather than limiting attention to the "river-routing" context, where single-sided connections are disallowed. For the minimum separation problem, we obtain O(lgN) time on a CREW PRAM or O(lgN / lglgN) time on a (common) CRCW PRAM, both with optimal work (processor- time product) of O(N), where N is the number of terminals. For the offset range problem, we obtain the same time and processor …

Development Of Object-Based Teleoperator Control For Unstructured Applications, Hyunki Cho

Theses and Dissertations

For multi-fingered end effectors in unstructured applications, the main issues are control in the presence of uncertainties and providing grasp stability and object manipulability. The suggested concept in this thesis is object based teleoperator control which provides an intuitive way to control the robot in terms of the grasped object and reduces the operator's conceptual constraints. The general control law is developed using a hierarchical control structure, i.e., human interface I gross motion control level in teleoperation control and fine motion control/object grasp stability in autonomous control. The gross motion control is required to provide the position/orientation of the Super …

Monte Carlo Simulations Of Photoemission Characteristics From Gaas And Diamond, Abhishek Srivastava

Electrical & Computer Engineering Theses & Dissertations

Monte Carlo based numerical simulations were performed to study photoemission from GaAs and diamond. The central goal was to assess the potential for NEA photoemission from diamond, and to predict its characteristics. The GaAs material system was also included in the simulation study to provide: (i) calibration and validation of the numerical model developed by carefully matching the simulation results with available experimental data, and (ii) quantitative comparisons between the response characteristics of diamond and the better known GaAs system.

Predictions of the energy distribution, temporal response and angular distribution of emitted electrons were obtained. Effects of various parameters, such …

Resource/Dataflow Graph Operating System Development, Sriram J. Coimbatore

Electrical & Computer Engineering Theses & Dissertations

Implementation of a new dataflow schedule model is the objective of this thesis. The dataflow model algorithm called the resource/dataflow graph model is implemented on a peer-to-peer communication network comprising of six personal computers. This dataflow model is implemented making use of an earlier dataflow model called ATAMM (Algorithm to Architecture Mapping Model) developed by ODU and National Aeronautics and Space Administration (NASA). Development issues include modification of the RDFG testbed operating system and a scheme to transfer data buffers using the ethernet channel from one processor to another processor. This, in turn, equips each sub-module of an application with …

An Empirical Comparison Of Area-Universal And Other Parallel Computing Networks, Ronald I. Greenberg, Lee Guan

Computer Science: Faculty Publications and Other Works

This paper provides empirical comparison of the communication capabilities of two area-universal networks, the fat-tree and the fat-pyramid, to the popular mesh and hypercube networks for parallel computation. While area-universal networks have been proven capable of simulating, with modest slowdown, any computation of any other network of comparable area, prior work has generally left open the question of how area-universal networks compare to other networks in practice. Comparisons are performed using techniques of throughput and latency analysis that have previously been applied to k-ary n-cube networks and using various existing models to equate the hardware cost of the networks being …

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 …

Neural Generalized Predictive Control For Real-Time Control, Donald I. Soloway

Electrical & Computer Engineering Theses & Dissertations

In this thesis a computationally efficient Generalized Predictive Control (GPC) algorithm is presented and implemented. The algorithm is more efficient than others because the number of iterations needed for convergence is significantly lower with Newton-Raphson. The main additional cost with Newton-Raphson algorithm is the calculation of the Hessian. This overhead is not a problem because of the reduced number of iterations, making the algorithm suitable for real-time control. For nonlinear control applications, a neural network is used as a dynamical system predictor leading to a Neural Generalized Predictive Control (NGPC) algorithm which is presented in detail in this thesis. An …

Visual Speech Recognition Using Multiple Deformable Lip Models, Devi Chandramohan

Electrical & Computer Engineering Theses & Dissertations

Motivated by the fact that human speech perception is a bimodal process (auditory and visual), several researchers have designed and implemented automatic speech recognition (ASR) systems consisting of both audio and visual subsystems, and shown improved performance relative to traditional purely auditory systems. Several visual speech reading approaches have used deformable templates to model the shape of a speaker's lips. Deformable templates are models of image objects, which can be deformed by adjusting a set of parameters to match the object in some optimal way, as defined by a cost function. Using a single deformable lip model has disadvantages such …

Speech Feature Computation For Visual Speech Articulation Training, Stefan Auberg

Electrical & Computer Engineering Theses & Dissertations

A new version of the Visual Speech Articulation Training Aid was implemented which provides real-time visual feedback for speech articulation training. This version was migrated to a Windows Multimedia PC from a previous version which used a Personal Computer (PC) system and additional specialized and expensive custom hardware. This new version will make the system more available to schools and private users. A new method was developed for computing spectral/temporal features which characterize the speech sounds. In addition to the typical frame-based spectral analysis parameters, the new method represents temporal changes of the spectrum with a small number of features. …

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.

Adaptive Integration Of Audio And Visual Information Using Discrete And Semi-Continuous Hidden Markov Models In Audiovisual Automatic Speech Recognition, Qin Su

Electrical & Computer Engineering Theses & Dissertations

An audiovisual semi-continuous hidden Markov model (HMM)-based Automatic Speech Recognition (ASR) system and an improved method of integrating audio and visual information in an audiovisual discrete HMM-based ASR system are investigated.

In the audiovisual discrete HMM, an adaptive integration formulation is employed, which incorporates the integration into the HMM at a pre-categorical stage. A visual weighting parameter is determined automatically, which allows the relative contribution of audio and visual information to be adjusted adaptively. Using an adaptive weight, the accuracy increased by 13% compared to the same model with no adaptive weight.

The semi-continuous HMM is a class of models …

Generalized Hidden Filter Markov Models Applied To Speaker Recognition, John M. Colombi

Theses and Dissertations

Classification of time series has wide Air Force, DoD and commercial interest, from automatic target recognition systems on munitions to recognition of speakers in diverse environments. The ability to effectively model the temporal information contained in a sequence is of paramount importance. Toward this goal, this research develops theoretical extensions to a class of stochastic models and demonstrates their effectiveness on the problem of text-independent (language constrained) speaker recognition. Specifically within the hidden Markov model architecture, additional constraints are implemented which better incorporate observation correlations and context, where standard approaches fail. Two methods of modeling correlations are developed, and their …

Application Of Autoregressive Moving Average Linear Prediction Filters To The Characterization Of Solar Wind-Magnetosphere Coupling, Carter N. Borst

Theses and Dissertations

Linear prediction filtering techniques have been used in studying the coupling processes between the solar wind and magnetosphere. The magnetosphere is a complex, dynamic system with at least two independent coupling methods for energy input, driven and unloading. Linear models were built and tested on the Bargatze data set, consisting of over 70 days of geomagnetic indices and solar wind data ordered in 34 intervals of increasing geomagnetic activity. Linear filtering techniques employing single-and multiple-input, autoregressive models predicted values of the magnetic index AL from solar wind data. The impulse response curves of the AL-coupling function groups showed amplitude peaks …

Intelligent Control Of Vehicles: Preliminary Results On The Application Of Learning Automata Techniques To Automated Highway System, Cem Unsal, John S. Bay, Pushkin Kachroo

Electrical & Computer Engineering Faculty Research

We suggest an intelligent controller for an automated vehicle to plan its own trajectory based on sensor and communication data received. Our intelligent controller is based on an artificial intelligence technique called learning stochastic automata. The automaton can learn the best possible action to avoid collisions using the data received from on-board sensors. The system has the advantage of being able to work in unmodeled stochastic environments. Simulations for the lateral control of a vehicle using this AI method provides encouraging results.