Computer Engineering Commons^™

My Collaboration With Raj Mittra: Contributions To The Theory Of Perfectly Matched Layers, Mustafa Kuzuoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

Use Of Characteristic Basis Function Method For Scattering From Terrain Profiles, Atacan Yağbasan, Celal Alp Tunç, Vakur B. Ertürk, Ayhan Altintas, Raj Mittra

Turkish Journal of Electrical Engineering and Computer Sciences

An integral equation (IE) based solution procedure is presented for the rigorous analysis of scattering from terrain profiles. The procedure uses characteristic basis function method (CBFM), which is hybridized with the forward-backward method (FBM), to reduce the storage requirements of the resultant Method of Moments (MoM) impedance matrix, as well as to accelerate the solution procedure. Numerical results in the form of induced current and scattered field are presented to assess the accuracy and efficiency of the solution procedure.

The Characteristic Basis Function Method (Cbfm): A Numerically Efficient Strategy For Solving Large Electromagnetic Scattering Problems, Eugenio Lucente, Gianluigi Tiberi, Agostino Monorchio, Giuliano Manara, Raj Mittra

Turkish Journal of Electrical Engineering and Computer Sciences

The objective of this paper is to describe a numerically efficient strategy for solving large electromagnetic scattering problems. This novel approach, termed as the Characteristic Basis Function Method (CBFM), is based on utilizing Characteristic Basic Functions (CBFs)-special functions defined on macro domains (blocks)-that include a relatively large number of conventional sub-domains discretized by using triangular or rectangular patches. The CBFs can be derived either analytically (from PO solutions), or by applying the conventional MoM. Use of these basis functions leads to a significant reduction in the number of unknowns, and results in a substantial size reduction of the MoM matrix. …

Dual-Band Split-Ring Antenna Design For Wlan Applications, S. Cumhur Başaran, Yunus E. Erdemli̇

Turkish Journal of Electrical Engineering and Computer Sciences

A dual-band microstrip antenna based on split-ring elements is introduced for WLAN (2.4/5.2 GHz) applications. The proposed split-ring antenna (SRA) has a compact novel design which provides about 2% impedance-bandwidth without a need for additional matching network. Analysis and design of the proposed microstrip antenna is carried out by means of full-wave simulators based on the finite-element method.

Comparison Of Rectangular And Cylindrical Fdtd Representations On A Ring Resonator Problem, Funda Akleman, Levent Sevgi̇

Turkish Journal of Electrical Engineering and Computer Sciences

The aim of this paper is to discuss rectangular and cylindrical representations of finite-difference time-domain (FDTD) method over characteristic tests and comparisons. A ring resonator is chosen as a canonical structure and modeled with both rectangular- and cylindrical-FDTD packages. Calibration against analytical exact solution derived in terms of cylindrical Bessel functions is also performed. It is shown that rectangular-FDTD with periodic boundary condition, where the computation domain is reduced, can also be applied in modeling circular structures.

Method Of Moments Solution By Using Sinc-Type Basis Functions For The Scattering From A Finite Number Of Conducting Strip Gratings, Taner Oğuzer, Fadil Kuyucuoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

A numerical method of moments (MoM) solution is applied to the electromagnetic scattering from a periodic finite conducting strip array when the incident electromagnetic plane wave E and H polarizations illuminate the grating. For such grating strip geometry, we deal with singular integral equations arising from Neumann and Dirichlet boundary conditions. MoM is applied using band-limited sinc functions as basis and testing functions. The Galerkin approach is followed in MoM formulation. The properties of the sinc function, with the infinite integral, are exploited in the computations of the main matrix elements. Also, the error in our approach goes to zero …

Comparison Of Basic Linear Filters In Extracting Auditory Evoked Potentials, Serap Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

In the present study, the performances of two well-known linear filtering techniques are compared for extraction of auditory Evoked Potential (EP) from a relatively small number of sweeps. Both experimental and simulated data are filtered by the two algorithms into two groups. Group A consists of Wiener filtering (WF) applications, where conventional WF and Coherence Weighted WF (CWWF)) have been assessed in combination with the Subspace Method (SM). Group B consists of the well-known adaptive filtering algorithms Least Mean Square (LMS), Recursive Least Square (RLS), and one-step Kalman filtering (KF). Both groups are tested with respect to signal-to-noise ratio (SNR) …

Zero Crossing Counter For Accuracy Improvement Of Fmcw Range Detection, Si̇nan Kurt, Şi̇mşek Demi̇r, Altunkan Hizal

Turkish Journal of Electrical Engineering and Computer Sciences

For civil and military purposes FMCW radars are widely used. The theoretical background is well-established. Nevertheless, improvement of various aspects of these radars is still required. Signal processing is one of the crucial points of the system which determines the capabilities of the radar. In this study a zero crossing detector implementation, which can be efficiently used for target detection and range calculation in short range FMCW range detector is proposed. The duration between consecutive zero-crossings are used as the data instead of the number of cycles per unit time. Experimental evaluation of its performance is also given.

A Novel Theoretical Procedure To Determine Absorption And Gain Coefficients In A Symmetric Single Step-Index Quantum Well Laser, Mustafa Temi̇z, Özgür Önder Karakilinç, Mehmet Ünal

Turkish Journal of Electrical Engineering and Computer Sciences

If the indices n_{II}, n_{I,III} of the regions, the thickness 2a of the active region (AR) and the wavelength \lambda for a single symmetric step-index quantum well laser (SSSIQWL) are given, the normalized propagation constant (NPC) \alpha is obtained. In this novel method, absorption and gain coefficients for the SSSIQWL have been obtained in terms of the NPCs \alpha in the even and odd fields, directly.

Online Tuning Of Set-Point Regulator With A Blending Mechanism Using Pi Controller, Engi̇n Yeşi̇l, Müjde Güzelkaya, İbrahi̇m Eksi̇n, Ö. Aydin Teki̇n

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a new control structure that exploits the advantages of one degree of freedom (1-DOF) and two degree of freedom (2-DOF) control structures with an online tuned set-point regulator with blending mechanism (SPR-BM) is proposed. In this structure, the filtered output of the reference and the pure reference signals are blended so that the overall performance of the system is ameliorated with respect to load disturbance rejection and set-point following. Internal Model Control (IMC) based PI controller is used as the primary controller and the blending dynamics are determined with the aim of producing a system output that …

A New Approach Using Temporal Radial Basis Function In Chronological Series, Mustapha Guezouri

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we present an extended form of Radial Basis Function network called Temporal-RBF (T-RBF) network. This extended network can be used in decision rules and classification in Spatio-Temporal domain applications, like speech recognition, economic fluctuations, seismic measurements and robotics applications. We found that such a network complies with relative ease to constraints such as capacity of universal approximation, sensibility of node, local generalisation in receptive field, etc. For an optimal solution based on a probabilistic approach with a minimum of complexity, we propose two TRBF models (1 and 2). Application to the problem of Mackey-Glass time series has …

Role Of Artificial Intelligence In The Reliability Evaluation Of Electric Power Systems, Chanan Singh, Lingfeng Wang

Turkish Journal of Electrical Engineering and Computer Sciences

Every reliability analysis effort, in some way, involves searching the state space of the system for those states that represent the events of interest, typically failure of the system or a given node to meet the demand. This essentially translates into a search procedure to efficiently identify states to be examined and then using a mechanism to evaluate these states. Traditionally, reliability analysis methods are based either on an implicit or explicit enumeration process or Monte Carlo sampling. More recently, methods based on artificial intelligence have been investigated both as an alternative to Monte Carlo for the search process as …

Dispersion Analysis Of The Adi-Fdtd And S-Fdtd Methods, Mehmet Kuşaf, Abdullah Y. Öztoprak

Turkish Journal of Electrical Engineering and Computer Sciences

Numerical dispersion performances of ADI-FDTD and S-FDTD methods have been compared. It has been shown that for time steps below the stability limits of the S-FDTD method it has much better dispersion performance compared with the ADI-FDTD method and that the S-FDTD method can be usefully employed for space increments in the order of \lambda/25 to \lambda/50.

Power Distortion Issues In Wind Turbine Power Systems Under Transient States, Tadeusz Lobos, Jacek Rezmer, Tomasz Sikorski, Zbigniew Waclawek

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper time-frequency methods have been investigated for complex investigations of transient states in wind power plants. Application of parallel processing in time and frequency domain brought new findings in description of wind power plants working under transient conditions. Proposed algorithms represents standard Short-Time Fourier Transform (STFT) as well as alternative methods associated with Cohen's class: Choi-Williams Distribution (CWD) and Zhao-Atlas-Marks Distribution (ZAMD). In order to explore advantages and disadvantages of the method several experiments were performed using model of squirrel-cage induction machine connected directly to the grid. Investigated phenomena concerned power distortion caused by switching-on capacitor banks and …

Evolutionary Algorithms For The Unit Commitment Problem, A. Şi̇ma Uyar, Belgi̇n Türkay

Turkish Journal of Electrical Engineering and Computer Sciences

This paper compares three evolutionary computation techniques, namely Steady-State Genetic Algorithms, Evolutionary Strategies and Differential Evolution for the Unit Commitment Problem. The comparison is based on a set of experiments conducted on benchmark datasets as well as on real-world data obtained from the Turkish Interconnected Power System. The results of two state-of-the-art evolutionary approaches, namely a Generational Genetic Algorithm and a Memetic Algorithm for the same benchmark datasets are also included in the paper for comparison. The tests show that Differential Evolution is the best performer among all approaches on the test data used in the paper. The performances of …

What Is Rcu, Fundamentally?, Paul E. Mckenney, Jonathan Walpole

Computer Science Faculty Publications and Presentations

Read-copy update (RCU) is a synchronization mechanism that was added to the Linux kernel in October of 2002. RCU achieves scalability improvements by allowing reads to occur concurrently with updates. In contrast with conventional locking primitives that ensure mutual exclusion among concurrent threads regardless of whether they be readers or updaters, or with reader-writer locks that allow concurrent reads but not in the presence of updates, RCU supports concurrency between a single updater and multiple readers. RCU ensures that reads are coherent by maintaining multiple versions of objects and ensuring that they are not freed up until all pre-existing read-side …

Evaluation Of Robocode As A Teaching Tool For Computer Programming, Arnold Hensman

Conference Papers

Robocode began as an educational tool to aid in learning Java programming. It has since evolved into something of a phenomenon, as the prospect of creating simple to complex virtual tanks appears to pose an attractive challenge to both novice and expert programmers alike. What started out as a teaching tool has grown into a worldwide network of competitors, all keen to prove that their ‘bot’ stands out from the crowd. Competitions are well organised and many Robocode events are a PR dream for the computing companies that sponsor them. Without a doubt, this easy to use application has sparked …

Self-Organizing Neural Architectures And Cooperative Learning In A Multiagent Environment, Dan Xiao, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Temporal-Difference–Fusion Architecture for Learning, Cognition, and Navigation (TD-FALCON) is a generalization of adaptive resonance theory (a class of self-organizing neural networks) that incorporates TD methods for real-time reinforcement learning. In this paper, we investigate how a team of TD-FALCON networks may cooperate to learn and function in a dynamic multiagent environment based on minefield navigation and a predator/prey pursuit tasks. Experiments on the navigation task demonstrate that TD-FALCON agent teams are able to adapt and function well in a multiagent environment without an explicit mechanism of collaboration. In comparison, traditional Q-learning agents using gradient-descent-based feedforward neural networks, trained with the …

A Two-Phase Approach To Interactivity Enhancement For Large-Scale Distributed Virtual Environments, Nguyen Binh Duong Ta, Suiping Zhou

Research Collection School Of Computing and Information Systems

Distributed virtual environments (DVEs) are distributed systems that allow multiple geographically distributed clients (users) to interact simultaneously in a computer-generated, shared virtual world. Applications of DVEs can be seen in many areas nowadays, such as online games, military simulations, collaborative designs, etc. To support large-scale DVEs with real-time interactions among thousands or even more distributed clients, a geographically distributed server architecture (GDSA) is generally needed, and the virtual world can be partitioned into many distinct zones to distribute the load among the servers. Due to the geographic distributions of clients and servers in such architectures, it is essential to efficiently …

Lazy Preservation: Reconstructing Websites From The Web Infrastructure, Frank Mccown

Computer Science Theses & Dissertations

Backup or preservation of websites is often not considered until after a catastrophic event has occurred. In the face of complete website loss, webmasters or concerned third parties have attempted to recover some of their websites from the Internet Archive. Still others have sought to retrieve missing resources from the caches of commercial search engines. Inspired by these post hoc reconstruction attempts, this dissertation introduces the concept of lazy preservation{ digital preservation performed as a result of the normal operations of the Web Infrastructure (web archives, search engines and caches). First, the Web Infrastructure (WI) is characterized by its preservation …

A Modular Kernel Linear Discriminant Analysis Of Gabor Features For Improved Face Recognition, Neeharika Gudur

Electrical & Computer Engineering Theses & Dissertations

Automatic face recognition is one of the major challenges in computer vision and pattern analysis. This thesis presents an efficient face recognition system that is robust with regards to changes in illumination, facial expressions and partial occlusions. Modular Kernel Linear Discriminant Analysis performed on Gabor Features obtained from the face images is employed for improving face recognition accuracy. A face image is pre-processed using the 2D Gabor wavelet transform to achieve invariance to illumination in images. Modular approaches that divide the pre-processed images into smaller sub-images provide improved accuracy, as the facial variations in an image are confined to local …

Neighborhood Defined Adaboost Based Mixture Of Color Components For Efficient Skin Segmentation, Ramya Reddy Maaram

Electrical & Computer Engineering Theses & Dissertations

A skin segmentation algorithm robust to illumination changes and skin-like backgrounds is developed in this thesis. So far skin pixel classification has been limited to only individual color spaces and there has not been a comprehensive evaluation of which color components or combination of color components would provide the best classification accuracy, Color components in a given color space form the feature set for the classification of skin pixels. The combination of the color components or the features present within a single color space may not be the best when it comes to skin pixel classification as the discriminatory power …

Ceg 220: Introduction To C Programming For Engineers I, Jay Dejongh

Computer Science & Engineering Syllabi

This course provides a general introduction to computers as a problem-solving tool using the C programming language. Emphasis is on algorithms and techniques useful to engineers. Topics include data representation, debugging, and program verification. 4 credit hours. Prerequisite: MTH 229 (Calculus I) or EGR 101 (Engineering Mathematics).

Cs 405/605: Introduction To Database Management Systems, Soon M. Chung

Computer Science & Engineering Syllabi

Survey of logical and physical aspects of database management systems. Entity Relationship, relational, object-oriented models for databases are presented. Physical implementation methods are discussed.

Cs 240: Computer Programming I, Dale E. Nelson

Computer Science & Engineering Syllabi

Basic concepts of programming and programming languages are introduced. Emphasis is on structured programming and stepwise refinement. Prerequisite: MTH 130 or MPL 5.

Cs 400/600: Computer Science, Eric Maston

Computer Science & Engineering Syllabi

This is the initial course in the understanding of data structures. This course focuses on data structures with abstract data types, such as trees, stacks, queues and graphs. The course will use projects, developed on UNIX, to create a deeper understanding of data structure and their use.

Cs 466/666: Introduction To Formal Languages, Guozhu Dong

Computer Science & Engineering Syllabi

CS 466/666 is an introduction to formal language and automata theory. In this course we will examine methods for defining syntax of languages and recognizing patterns: the syntax of languages can be defined using grammars and patterns accepted by finite state machines. Along with presenting the fundamentals of these two topics, the course will develop and investigate the relationships between language definition and pattern recognition. The text will be the third edition of Languages and Machines: An Introduction to the Theory of Computer Science, by Thomas Sudkamp.

Cs 208: Computer Programming For Business I, Dennis Kellermeier

Computer Science & Engineering Syllabi

CS 208 is the first of a two quarter sequence in programming for business students. It is required for Management Information Science majors. The courses are designed to help students achieve a high degree of facility in intermediate level programming. This course assumes students have never written a program before.

Cs 141: Computer Programming - I, Michael Ondrasek

Computer Science & Engineering Syllabi

This course provides a general introduction to the fundamentals of computer programming. Examples from and applications to a broad range of problems are given. No prior knowledge of programming is assumed. The concepts covered will be applied to the Java programming language. Students must register for both lecture and one laboratory section. 4 credit hours. Prerequisite: MTH 127 (College Algebra) or equivalent.

Cs 790: Information Theory, Machine Learning And Statistics, Shaojun Wang

Computer Science & Engineering Syllabi

Information theory deals with encoding data in order to transmit it correctly and effectively. Statistics and machine learning deal with estimating models of data and predicting future observations. ls there any relationship between the two? It turns out, perhaps not surprisingly, that the most compact encoding of the data is by the probabilistic model that describes it best. In other words, there is a fundamental link between information and probability.

This course starts with the basic notions of information theory and explores its relationship to machine learning and statistics. The course will have a strong theoretical component, but will also …