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Articles 4981 - 5010 of 5273
Full-Text Articles in Computer Sciences
Decentralized Neural Network Control Of A Class Of Large-Scale Systems With Unknown Interconnection, Wenxin Liu, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow
Decentralized Neural Network Control Of A Class Of Large-Scale Systems With Unknown Interconnection, Wenxin Liu, Jagannathan Sarangapani, Donald C. Wunsch, Mariesa Crow
Electrical and Computer Engineering Faculty Research & Creative Works
A novel decentralized neural network (DNN) controller is proposed for a class of large-scale nonlinear systems with unknown interconnections. The objective is to design a DNN for a class of large-scale systems which do not satisfy the matching condition requirement. The NNs are used to approximate the unknown subsystem dynamics and the interconnections. The DNN is designed using the back stepping methodology with only local signals for feedback. All of the signals in the closed loop (system states and weights estimation errors) are guaranteed to be uniformly ultimately bounded and eventually converge to a compact set.
Discrete-Time Neural Network Output Feedback Control Of Nonlinear Systems In Non-Strict Feedback Form, Pingan He, Jagannathan Sarangapani
Discrete-Time Neural Network Output Feedback Control Of Nonlinear Systems In Non-Strict Feedback Form, Pingan He, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
An adaptive neural network (NN)-based output feedback controller is proposed to deliver a desired tracking performance for a class of discrete-time nonlinear systems, which is represented in non-strict feedback form. The NN backstepping approach is utilized to design the adaptive output feedback controller consisting of: 1) a NN observer to estimate the system states with the input-output data, and 2) two NNs to generate the virtual and actual control inputs, respectively. The non-causal problem in the discrete-time backstepping design is avoided by using the universal NN approximator. The persistence excitation (PE) condition is relaxed both in the NN observer and …
Neural Network Controller For Manipulation Of Micro-Scale Objects, Vijayakumar Janardhan, Pingan He, Jagannathan Sarangapani
Neural Network Controller For Manipulation Of Micro-Scale Objects, Vijayakumar Janardhan, Pingan He, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A novel reinforcement learning-based neural network (RLNN) controller is presented for the manipulation and handling of micro-scale objects in a microelectromechanical system (MEMS). In MEMS, adhesive, surface tension, friction and van der Waals forces are dominant. Moreover, these forces are typically unknown. The RLNN controller consists of an action NN for compensating the unkoown system dynamics, and a critic NN to tune the weights of the action NN. Using the Lyapunov approach, the uniformly ultimate houndedness (UUB) of the closed-loop tracking error and weight estimates are shown by using a novel weight updates. Simulation results are presented to substantiate the …
Developing Software For Wound Measurement, Savo Kordic
Developing Software For Wound Measurement, Savo Kordic
Theses : Honours
Chronic wounds such as leg ulcers, pressure ulcers and diabetic ulcers affect many thousands of people in Australia. In addition to the costs of these wounds in terms of human suffering, loss of income and resources, there are costs related to the treatment of ulcers. Thus, there is a genuine need to develop an accurate and a fully objective application for wound measurement. The aim of this project was to create software for the measurement of wounds. In achieving this goal, several issues were addressed: an accurate measurement method capable of detecting small changes in an open wound surface area, …
An Implicit Surface Modeling Technique Based On A Modular Neural Network Architecture, Manuel Carcenac
An Implicit Surface Modeling Technique Based On A Modular Neural Network Architecture, Manuel Carcenac
Turkish Journal of Electrical Engineering and Computer Sciences
Independently from artificial intelligence applications, an artificial neural network can be viewed as a powerful tool for function reconstruction. Previous papers used this property to model an implicit surface out of some control points by reconstructing its underlying scalar field. Such an approach requests the neural network to memorize the control points, which has turned problematic for complex surfaces. In our paper, we show that this problem can be efficiently tackled by adapting the architecture of the neural network to the features compounding the surface: by learning first these features independently and then blending them gradually together, our modular architecture …
Mining Classification Rules By Using Genetic Algorithms With Non-Random Initial Population And Uniform Operator, Korkut Koray Gündoğan, Bi̇lal Alataş, Ali̇ Karci
Mining Classification Rules By Using Genetic Algorithms With Non-Random Initial Population And Uniform Operator, Korkut Koray Gündoğan, Bi̇lal Alataş, Ali̇ Karci
Turkish Journal of Electrical Engineering and Computer Sciences
Classification is a supervised learning method that induces a classification model from a database and is one of the most commonly applied data mining task. The frequently employed techniques are decision tree or neural network-based classification algorithms. This work presents an efficient genetic algorithm (GA) for classification rule mining technique that discovers comprehensible IF-THEN rules using a generalized uniform population method and a uniform operator inspired from the uniform population method. Initial population is generated by methodically eliminating the randomness by generalized uniform population method. In the subsequence generations, genetic diversity is ensured and premature convergence is prevented by the …
Real-Time Classification Algorithm For Recognition Of Machine Operating Modes By Use Of Self-Organizing Maps, Gancho Vachkov, Yuhiko Kiyota, Koji Komatsu, Satoshi Fujii
Real-Time Classification Algorithm For Recognition Of Machine Operating Modes By Use Of Self-Organizing Maps, Gancho Vachkov, Yuhiko Kiyota, Koji Komatsu, Satoshi Fujii
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper a new algorithm for classification and real-time recognition of different a-priorily assumed operating modes for construction machines is proposed. This algorithm utilizes the effectiveness of the Self-Organizing Maps (SOM) for creating the so called Separation Models, that are able to distinguish each operating mode separately. After training, these models are used in a real-time procedure, which calculates at each sampling time the minimal Euclidean distances from the current data point to a certain node of each SOM. Then the separation model (represented by a respective SOM) that has the least minimal distance to this data point defines …
The 7 C'S For Creating Living Software: A Research Perspective For Quality-Oriented Software Engineering, Mehmet Akşi̇t
The 7 C'S For Creating Living Software: A Research Perspective For Quality-Oriented Software Engineering, Mehmet Akşi̇t
Turkish Journal of Electrical Engineering and Computer Sciences
This article proposes the 7 C's for realizing quality-oriented software engineering practices. All the desired qualities of this approach are expressed in short by the term living software. The 7 C's are: Concern-oriented processes, Canonical models, Composable models, Certifiable models, Constructible models, Closure property of models and Controllable models. Each C is explained by the help of a set of definitions, a short overview of the background work and the problems that software engineers may experience in realizing the corresponding C. Further, throughout the article, a software development example is presented for illustrating the realization of the 7 C's. Finally, …
An Information System For Streamlining Software Development Process, Serkan Nalbant
An Information System For Streamlining Software Development Process, Serkan Nalbant
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper an information system to be employed by software development organizations is proposed, which automates software development process. The proposed system aims to lower cost, improve schedule performance and enhance quality of the software projects by the means of automation and unifying of operational information. The characteristics of the proposed system are described. Furthermore, its use is illustrated via the explanation of an exemplary software system called PACE that serves as an information system for planning, controlling, measuring and improving software development process and projects. The relationship of PACE with Software Capability Maturity Model (CMM) is also provided.
A Platform For Software Engineering Course Projects, Bi̇rol Aygün
A Platform For Software Engineering Course Projects, Bi̇rol Aygün
Turkish Journal of Electrical Engineering and Computer Sciences
The importance of projects in software engineering courses is well known. Both synthetic and real-life projects have various advantages and disadvantages. Our aim was to create a framework where students can develop projects which reflect some of the complexities of real-life, involving many concurrent, interacting, asynchronous processes, each in a different stage of development, with wide temporal differences among them - some occurring within millisconds of each other and others executing sporadically over much longer periods. In this project, which was carried out in different arrangements in several software engineering courses in three universities, the students developed both the sub- …
A Pattern Based Approach To Web Design Formalization, Ahmet Sikici, Yasemi̇n Topaloğlu
A Pattern Based Approach To Web Design Formalization, Ahmet Sikici, Yasemi̇n Topaloğlu
Turkish Journal of Electrical Engineering and Computer Sciences
World Wide Web is a global information network that affects many fields of our lives. The distributed, interlinked, visual and heterogeneous structure of the web makes it an irregular development environment. In this paper we propose a pattern based approach for increasing the effectiveness of development for the Web environment. This approach is based on the representation of the core meaning of each design as a set of patterns and requires the formulation of abstract solutions in a mathematical precision. This way not only reusable design experience will be codified unambiguously, but a smooth transition between the design and implementation …
An Agile Information Systems Development Method In Use, Mehmet Nafi̇z Aydin, Frank Harmsen, Kees Van Slooten, Robert Stegwee
An Agile Information Systems Development Method In Use, Mehmet Nafi̇z Aydin, Frank Harmsen, Kees Van Slooten, Robert Stegwee
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, agile information systems development methods, agile methods in short, have got considerable attention from practitioners. One of the reasons seems that agile methods, to some degree, can be adaptable to different project situations. However, little empirical research has been conducted on this subject. The major goal of this research is to identify which aspects of agile methods are perceived as most critical and difficult to realize and how such aspects are adapted in practice. To reach this goal we studied the working practices concerning the adaptation of an agile method in the IT department of one of the leading …
A Robustness Analysis Of Game-Theoretic Cdma Power Control, Xingzhe Fan, Murat Arcak, John T. Wen
A Robustness Analysis Of Game-Theoretic Cdma Power Control, Xingzhe Fan, Murat Arcak, John T. Wen
Turkish Journal of Electrical Engineering and Computer Sciences
This paper studies robustness of a gradient-type CDMA uplink power control algorithm with respect to disturbances and time-delays. This problem is of practical importance because unmodeled secondary interference effects from neighboring cells play the role of disturbances, and propagation delays are ubiquitous in wireless data networks. We first show L_p-stability, for p \in [1,\infity], with respect to additive disturbances. We pursue L_{\infity}-stability within the input-to-state stability (ISS) framework of Sontag [7], which makes explicit the vanishing effect of the initial conditions. Next, using the ISS property and a loop transformation, we prove that global asymptotic stability is preserved for sufficiently …
Global Stability Analysis Of An End-To-End Congestion Control Scheme For General Topology Networks With Delay, Tansu Alpcan, Tamer Başar
Global Stability Analysis Of An End-To-End Congestion Control Scheme For General Topology Networks With Delay, Tansu Alpcan, Tamer Başar
Turkish Journal of Electrical Engineering and Computer Sciences
We analyze the stability properties of an end-to-end congestion control scheme under fixed heterogeneous delays, and for general network topologies. The scheme analyzed is based on the congestion control game of [1], with the starting point being the unique Nash equilibrium of that game. We prove global stability of this solution (and hence of the congestion control algorithm) under a mild symmetricity condition. We further demonstrate the stability of the algorithm numerically for various delays, user numbers, and topologies
Flow Controller Design And Performance Analysis For Self-Similar Network Traffic, Peng Yan
Flow Controller Design And Performance Analysis For Self-Similar Network Traffic, Peng Yan
Turkish Journal of Electrical Engineering and Computer Sciences
Recent studies of high-resolution traffic measurement discovered the self-similarity in both LAN and WAN traffic. In this paper, we introduce a two-degree of freedom rate based flow controller, which includes a robust H^{\infity} control block and an LMMSE based capacity predictor. The former part can guarantee the robust stability against time-varying time delay uncertainties and the latter improves the transient response by predicting the self-similar cross-traffic. Implementation issues are discussed and performance analysis is provided to validate our design. We also investigate the prediction and control in larger time scale which is more applicable for the real network environment
Optimum And Suboptimum Blind Channel And Symbol Estimation For Siso Channels, T. Engi̇n Tuncer
Optimum And Suboptimum Blind Channel And Symbol Estimation For Siso Channels, T. Engi̇n Tuncer
Turkish Journal of Electrical Engineering and Computer Sciences
We present three methods for blind channel and symbol identification from a single or multi-block observation. These methods are deterministic approaches suitable for the identification of quickly changing wireless channels. The first method uses the finite alphabet property and it has good performance even for noisy observations. It requires only a single data frame, which is a unique feature of the method. This method can also be used to identify the channel order. For multi-block observations, we present the maximal ratio combining cross relation (MRCCR) method. It is an optimum approach in terms of instantaneous SNR and is based on …
Spatiotemporal Databases: Models For Attracting Students To Research, Ágnes Bércesné Novák, Peter Revesz, Zsolt Tuza
Spatiotemporal Databases: Models For Attracting Students To Research, Ágnes Bércesné Novák, Peter Revesz, Zsolt Tuza
School of Computing: Conference and Workshop Papers
In higher education professors often make much effort to introduce their students to research. Unfortunately, the present standard database systems curriculum is composed of well-settled subjects that do not lead to research. The challenge is to bring the research frontier closer to students at beginner level. In this paper we describe how it can be done in the area of spatiotemporal databases. We propose a new database systems curriculum and illustrate its benefits by mentioning several highly succsesful student projects in some recent experimental introductory database systems courses that followed the new curriculum.
A Computer-Based Articulation Training Aid For Short Words (Cata), Mukund Devarajan
A Computer-Based Articulation Training Aid For Short Words (Cata), Mukund Devarajan
Electrical & Computer Engineering Theses & Dissertations
Several improvements in the vowel articulation training aid (VATA) are described, as well as the efforts to extend the visual feedback system to operate with short words in the form of consonant, vowel and consonant (CVC). The extended version of the visual feedback system is referred to as CATA (Computer-based Articulation Training Aid); the vowel version of the aid (VATA) only operates with ten American English monopthong vowels. Improvements in VATA include the use of a neural network (NN) recognizer method to prune a large database of vowel recordings to eliminate noisy and/or mispronounced tokens. The spectral jitter problem, previously …
Unidirectional Cordic For Efficient Computation Of Trigonometric And Hyperbolic Functions, Satish Ravichandran
Unidirectional Cordic For Efficient Computation Of Trigonometric And Hyperbolic Functions, Satish Ravichandran
Electrical & Computer Engineering Theses & Dissertations
CORDIC (Coordinate Rotation Digital Computer) is an iterative algorithm to compute values of trigonometric, logarithmic and transcendental functions by performing vector rotations, which can be implemented with only shift and add operations in a digital system. CORDIC algorithms are extensively used in the areas of digital signal processing, digital image processing and artificial neural networks. A new technique, named unidirectional CORDIC, for efficient computation of trigonometric and hyperbolic functions is presented in this thesis. In the conventional CORDIC algorithm, the vector rotations are performed in both clockwise and counterclockwise directions, but in the unidirectional CORDIC the vectors are rotated only …
One-Layer Neural-Network Controller With Preprocessed Inputs For Autonomous Underwater Vehicles, Sarangapani Jagannathan, Gustavo Galan
One-Layer Neural-Network Controller With Preprocessed Inputs For Autonomous Underwater Vehicles, Sarangapani Jagannathan, Gustavo Galan
Electrical and Computer Engineering Faculty Research & Creative Works
Navigating, guiding, and controlling autonomous underwater vehicles (AUVs) are challenging and difficult tasks compared to the autonomous surface-level operations. Controlling the motion of such vehicles require the estimation of unknown hydrodynamic forces and moments and disturbances acting on these vehicles in the underwater environment. in this paper, a one-layer neural-network (NN) controller with preprocessed input signals is designed to control the vehicle track along a desired trajectory, which is specified in terms of desired position and attitude. in the absence of unknown disturbances and modeling errors, it is shown that the tracking error system is asymptotically stable. in the presence …
Parallel Implementation Of A Face Recognition [Sic] System Based On Modular Pca Approach, Rajkiran Gottumukkal
Parallel Implementation Of A Face Recognition [Sic] System Based On Modular Pca Approach, Rajkiran Gottumukkal
Electrical & Computer Engineering Theses & Dissertations
This thesis describes research in automated methods for the recognition of human faces. The research is driven by the need to design a method, which would ensure high accuracy under the conditions of facial expression, illumination and pose variations. The resulting method is able to cope with uncontrolled nature of facial expression, illumination and head rotations. The main novelty of this work is the idea that some of the local facial features do not vary even when the facial expression, illumination and pose vary. This idea is applied to the existing principle component analysis lPCA) method to arrive at a …
A Combinatorial Technique For Face Detection Based On Color And Statistical Analysis, Harishwaran Hariharan
A Combinatorial Technique For Face Detection Based On Color And Statistical Analysis, Harishwaran Hariharan
Electrical & Computer Engineering Theses & Dissertations
Automatic detection of faces from video sequences is an important task in security applications. The number, location, size and orientation of human faces in a video frame are unpredictable and can vary from frame to frame. A face detection algorithm for color images in the presence of varying lighting conditions and complexity in background relying upon color and statistical analysis is presented in this thesis. The new method detects skin regions over the entire image and then classifies the skin regions as faces and non-faces. Segmentation of skin regions is performed by a novel color space merging procedure named Integrated …
Inquisitive Pattern Recognition, Amy L. Magnus
Inquisitive Pattern Recognition, Amy L. Magnus
Theses and Dissertations
The Department of Defense and the Department of the Air Force have funded automatic target recognition for several decades with varied success. The foundation of automatic target recognition is based upon pattern recognition. In this work, we present new pattern recognition concepts specifically in the area of classification and propose new techniques that will allow one to determine when a classifier is being arrogant. Clearly arrogance in classification is an undesirable attribute. A human is being arrogant when their expressed conviction in a decision overstates their actual experience in making similar decisions. Likewise given an input feature vector, we say …
Personality Types In Software Engineering, Luiz Fernando Capretz
Personality Types In Software Engineering, Luiz Fernando Capretz
Electrical and Computer Engineering Publications
No abstract provided.
Parametrically Tunable Audio Shelving And Equalizing Ladder Wave Digital Filters, S. A. Samad
Parametrically Tunable Audio Shelving And Equalizing Ladder Wave Digital Filters, S. A. Samad
Turkish Journal of Electrical Engineering and Computer Sciences
Parametrically tunable audio equalizers are conventionally realized using allpass digital filter networks. They consist of first-order shelving filters and second-order equalizing filters. In this paper, ladder wave digital filters (WDFs) with parametrically tunable coefficients are proposed as shelving and equalizing filters. Similar to the allpass realization, the transfer function power complementary property of WDFs is used to obtain efficient shelving and equalizing filters. However, unlike the allpass structures, the transfer function and the tunable parameters of the ladder WDF are derived from the analog filter equivalent of the digital shelving and equalizing filters. For the shelving WDF, the cut-off frequency …
Neuro Emission Controller For Minimizing Cyclic Dispersion In Spark Ignition Engines, Pingan He, Jagannathan Sarangapani
Neuro Emission Controller For Minimizing Cyclic Dispersion In Spark Ignition Engines, Pingan He, Jagannathan Sarangapani
Electrical and Computer Engineering Faculty Research & Creative Works
A novel neural network (NN) controller is developed to control spark ignition (SI) engines at extreme lean conditions. The purpose of neurocontroller is to reduce the cyclic dispersion at lean operation even when the engine dynamics are unknown. The stability analysis of the closed-loop control system is given and the boundedness of all signals is ensured. Results demonstrate that the cyclic dispersion is reduced significantly using the proposed controller. The neuro controller can also be extended to minimize engine emissions with high EGR levels, where similar complex cyclic dynamics are observed. Further, the proposed approach can be applied to control …
Million City Traveling Salesman Problem Solution By Divide And Conquer Clustering With Adaptive Resonance Neural Networks, Samuel A. Mulder, Donald C. Wunsch
Million City Traveling Salesman Problem Solution By Divide And Conquer Clustering With Adaptive Resonance Neural Networks, Samuel A. Mulder, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
The Traveling Salesman Problem (TSP) is a very hard optimization problem in the field of operations research. It has been shown to be NP-complete and is an often-used benchmark for new optimization techniques. One of the main challenges with this problem is that standard, non-AI heuristic approaches such as the Lin-Kernighan algorithm (LK) and the chained LK variant are currently very effective and in wide use for the common fully connected, Euclidean variant that is considered here. This paper presents an algorithm that uses adaptive resonance theory (ART) in combination with a variation of the Lin-Kernighan local optimization algorithm to …
Welcome To The Special Issue: The Best Of The Best, Donald C. Wunsch, Mike Hasselmo, De Liang Wang, Ganesh K. Venayagamoorthy
Welcome To The Special Issue: The Best Of The Best, Donald C. Wunsch, Mike Hasselmo, De Liang Wang, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
No abstract provided.
Improving The Security And Flexibility Of One-Time Passwords By Signature Chains, Kemal Biçakci, Nazi̇fe Baykal
Improving The Security And Flexibility Of One-Time Passwords By Signature Chains, Kemal Biçakci, Nazi̇fe Baykal
Turkish Journal of Electrical Engineering and Computer Sciences
While the classical attack of ``monitor the network and intercept the password'' can be avoided by advanced protocols like SSH, one-time passwords are still considered a viable alternative or a supplement for software authentication since they are the only ones that safeguard against attacks on insecure client machines. In this paper by using public-key techniques we present a method called signature chain alternative to Lamport's hash chain to improve security and flexibility of one-time passwords. Our proposition improves the security because first, like other public-key authentication protocols, the server and the user do not share a secret, thereby eliminating attacks …
Initiatory Electrons In Compressed Gases In Positive Polarity, Mohammed Messaad, Mustapha Tioursi
Initiatory Electrons In Compressed Gases In Positive Polarity, Mohammed Messaad, Mustapha Tioursi
Turkish Journal of Electrical Engineering and Computer Sciences
This paper deals with the nature of seed electron sources in compressed N_2 for positive polarity. We present an experimental procedure that provides evidence of the fact that collisional detachment from negative ions plays the most important role in the supply of seed electrons. Conditioning phenomena in compressed SF_6, N_2 and air have been simulated under positive lightning impulses for point-plane geometry.