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Articles 9901 - 9930 of 12094
Full-Text Articles in Entire DC Network
User Authentication And Related Topics: An Annotated Bibliography, Eugene H. Spafford, Stephen A. Weeber
User Authentication And Related Topics: An Annotated Bibliography, Eugene H. Spafford, Stephen A. Weeber
Department of Computer Science Technical Reports
No abstract provided.
Methodologies For Voltage Contingency Ranking, James Matthew Kulaga
Methodologies For Voltage Contingency Ranking, James Matthew Kulaga
Department of Electrical and Computer Engineering Technical Reports
Contingency studies in interconnected electric power systems are performed to assess the capability of a system to withstand disturbances caused by equipment outages and other factors, and are relevant to the area of power system security. Due to the large size and complexity of modern power systems, accurate techniques for measuring the effect of line contingencies are often time consuming and impose a heavy computational burden. Thus, ranking methods are used to define a subset of the most severe contingencies to be studied in full detail. Contingencies are classified into voltage contingencies and power contingencies; the term voltage contingency refers …
Optimal Parallel Algorithms For Periods, Palindromes And Squares (Preliminary Version), Alberto Apostolico, Dany Breslauer, Zvi Galil
Optimal Parallel Algorithms For Periods, Palindromes And Squares (Preliminary Version), Alberto Apostolico, Dany Breslauer, Zvi Galil
Department of Computer Science Technical Reports
No abstract provided.
An Organization Of Sparse Gauss Elimination For Solving Pdes On Distributed Memory Machines, Mo Mu, John R. Rice
An Organization Of Sparse Gauss Elimination For Solving Pdes On Distributed Memory Machines, Mo Mu, John R. Rice
Department of Computer Science Technical Reports
No abstract provided.
How To Count Quickly And Accurately: A Unified Analysis Of Probabilistic Counting And Other Related Problems, Peter Kirschenhofer, Helmut Prodinger, Wojciech Szpankowski
How To Count Quickly And Accurately: A Unified Analysis Of Probabilistic Counting And Other Related Problems, Peter Kirschenhofer, Helmut Prodinger, Wojciech Szpankowski
Department of Computer Science Technical Reports
No abstract provided.
A Declarative View Of Inheritance In Logic Programming, M. Bugliesi
A Declarative View Of Inheritance In Logic Programming, M. Bugliesi
Department of Computer Science Technical Reports
No abstract provided.
Unstructured Scheduling In Parallel Pde Sparse Solvers On Distributed Memory Machines, Mo Mu, John R. Rice
Unstructured Scheduling In Parallel Pde Sparse Solvers On Distributed Memory Machines, Mo Mu, John R. Rice
Department of Computer Science Technical Reports
No abstract provided.
Uniform System For Accident Reporting, Jorge A. Vanegas
Uniform System For Accident Reporting, Jorge A. Vanegas
Indiana Local Technical Assistance Program (LTAP) Publications
This report presents the results of Project 91-08 Task 5, Project 1, Part III: Uniform System for Accident Reporting.
Quadratic Spline Collocation Methods For Elliptic Partial Differential Equations, Christina C. Christara
Quadratic Spline Collocation Methods For Elliptic Partial Differential Equations, Christina C. Christara
Department of Computer Science Technical Reports
No abstract provided.
Neural Networks For Constrained Optimization Problems, Walter E. Lillo, Stefen Hui, Stanislaw H. Zak
Neural Networks For Constrained Optimization Problems, Walter E. Lillo, Stefen Hui, Stanislaw H. Zak
Department of Electrical and Computer Engineering Technical Reports
This paper is concerned with utilizing neural networks and analog circuits to solve constrained optimization problems. A novel neural network architecture is proposed for solving a class of nonlinear programming problems. The proposed neural network, or more precisely a physically realizable approximation, is then used to solve minimum norm problems subject to linear constraints. Minimum norm problems have many applications in various areas, but we focus on their applications to the control of discrete dynamic processes. The applicability of the proposed neural network is demonstrated on numerical examples.
Neural Networks For Constrained Optimization Problems, Walter E. Lillo, Stefen Hui, Stanislaw H. Zak
Neural Networks For Constrained Optimization Problems, Walter E. Lillo, Stefen Hui, Stanislaw H. Zak
Department of Electrical and Computer Engineering Technical Reports
This paper is concerned with utilizing neural networks and analog circuits to solve constrained optimization problems. A novel neural network architecture is proposed for solving a class of nonlinear programming problems. The proposed neural network, or more precisely a physically realizable approximation, is then used to solve minimum norm problems subject to linear constraints. Minimum norm problems have many applications in various areas, but we focus on their applications to the control of discrete dynamic processes. The applicability of the proposed neural network is demonstrated on numerical examples
Generalized 'Probe' Model For Arbitrary Dephasing Mechanisms, Supriyo Datta
Generalized 'Probe' Model For Arbitrary Dephasing Mechanisms, Supriyo Datta
Department of Electrical and Computer Engineering Technical Reports
It has been shown earlier that in the linear response regime, dephasing by point scatterers (within the self-consistent Born approximation) can be visualized in terms of point voltage probes attached to each space and energy coordinate (r,E). In this paper we derive a generalized linear response equation starting from the non-equilibrium Green function formalism that can be used to describe any dephasing process in any approximation. The dephasing is characterized by a ‘reservoir function’ which can be evaluated from the self-energy. The linear response equation can be visualized in terms of voltage probes but with individual probes connected to each …
Computer Vision, Descriptive Geometry, And Classical Mechanics, Christoph M. Hoffmann
Computer Vision, Descriptive Geometry, And Classical Mechanics, Christoph M. Hoffmann
Department of Computer Science Technical Reports
No abstract provided.
How To Compute Offsets Without Self-Intersection, Ching-Shoei Chiang, Christoph M. Hoffmann, Robert E. Lynch
How To Compute Offsets Without Self-Intersection, Ching-Shoei Chiang, Christoph M. Hoffmann, Robert E. Lynch
Department of Computer Science Technical Reports
No abstract provided.
Data Structures And Sparsity In A Digital Simulation Of An Hvdc Link, Mark Timothy Luehmann
Data Structures And Sparsity In A Digital Simulation Of An Hvdc Link, Mark Timothy Luehmann
Department of Electrical and Computer Engineering Technical Reports
An earlier algorithm for the detailed simulation of the High Voltage Direct Current (HVDC) link using the tensor approach was modified to improve the runtime speed. The runtime, approximately eleven percent that of the original algorithm, was improved by employing sparsity techniques, restructuring the state matrix, and condensing subroutines. The readability of the code was accomplished by a modular programming approach. This research was done for a two-terminal simulation, but could be expanded and modified to include multiterminal simulations.
On Solving Constrained Optimization Problems With Neural Networks : A Penalty Function Method Approach, Walter E. Lillo, Mei Heng Loh, Stefen Hui, Stanislaw H. Zak
On Solving Constrained Optimization Problems With Neural Networks : A Penalty Function Method Approach, Walter E. Lillo, Mei Heng Loh, Stefen Hui, Stanislaw H. Zak
Department of Electrical and Computer Engineering Technical Reports
This paper is concerned with utilizing analog circuits to solve various linear and nonlinear programming problems. The dynamics of these circuits are analyzed. Then, the previously proposed circuit implementations for solving optimization problems are examined. A new nonlinear programming network and its circuit implementation is then introduced which utilizes the nonlinearities to eliminate the problems encountered in previous circuit implementations.
Shortest Path Computations In S-Graphs, Greg N. Frederickson, Susanne E. Hambrusch, Hung-Yi Tu
Shortest Path Computations In S-Graphs, Greg N. Frederickson, Susanne E. Hambrusch, Hung-Yi Tu
Department of Computer Science Technical Reports
No abstract provided.
Collaborating Pde Solvers, H. S. Mcfaddin, John R. Rice
Collaborating Pde Solvers, H. S. Mcfaddin, John R. Rice
Department of Computer Science Technical Reports
No abstract provided.
Numerical Quadrature For General Two-Dimensional Domains, James V. Lambers, John R. Rice
Numerical Quadrature For General Two-Dimensional Domains, James V. Lambers, John R. Rice
Department of Computer Science Technical Reports
No abstract provided.
Laser Bandwidth-Induced Fluctuations In The Intensity Transmitted By A Fabry-Perot Interferometer, Gerhard Klimeck, Daniel Elliott, M. Hamilton
Laser Bandwidth-Induced Fluctuations In The Intensity Transmitted By A Fabry-Perot Interferometer, Gerhard Klimeck, Daniel Elliott, M. Hamilton
Birck and NCN Publications
We have measured the power spectrum of the intensity Auctuations of light transmitted by a Fabry- Perot interferometer when the input field is the real Gaussian field. The real Gaussian field is a field characterized by real, random (Gaussian) amplitude Auctuations. The bandwidth of the real Gaussian field was varied, taking on values less than that of the interferometer, as well as greater. Comparisons of the measured spectra with calculated spectra are quite satisfactory. Of special interest is a feature in the spectra centered at the laser-interferometer detuning frequency.
The Ganith Algebraic Geometry Toolkit V 1.0, Chanderjit Bajaj, Andrew V. Royappa
The Ganith Algebraic Geometry Toolkit V 1.0, Chanderjit Bajaj, Andrew V. Royappa
Department of Computer Science Technical Reports
No abstract provided.
The Vaidak Medical Imaging And Model Reconstruction Toolkit, Brian Bailey, Chanderjit Bajaj, Malcolm C. Fields
The Vaidak Medical Imaging And Model Reconstruction Toolkit, Brian Bailey, Chanderjit Bajaj, Malcolm C. Fields
Department of Computer Science Technical Reports
No abstract provided.
Computer Viruses And Ethics, Eugene H. Spafford
Computer Viruses And Ethics, Eugene H. Spafford
Department of Computer Science Technical Reports
No abstract provided.
Using Algebraic Geometry For Multivariate Hermite Interpolation, Chanderjit L. Bajaj
Using Algebraic Geometry For Multivariate Hermite Interpolation, Chanderjit L. Bajaj
Department of Computer Science Technical Reports
No abstract provided.
On Surface Design With Implicit Algebraic Surfaces (Ph.D. Thesis), Insung Ihm
On Surface Design With Implicit Algebraic Surfaces (Ph.D. Thesis), Insung Ihm
Department of Computer Science Technical Reports
No abstract provided.
Decompositions Of Polyhedra In Three Dimensions (Ph.D. Thesis), Tamal Krishna Dey
Decompositions Of Polyhedra In Three Dimensions (Ph.D. Thesis), Tamal Krishna Dey
Department of Computer Science Technical Reports
No abstract provided.
Consensual Neural Networks, Jon A. Benediktsson, Okan K. Ersoy, Philip H. Swain
Consensual Neural Networks, Jon A. Benediktsson, Okan K. Ersoy, Philip H. Swain
Department of Electrical and Computer Engineering Technical Reports
A new neural network architecture is proposed and applied in classification of data from multiple sources. The new architecture is called a consensual neural network and its relation to hierarchical and ensemble neural networks is discussed. The consensual neural network architecture is based on statistical consensus theory and involves using non-linearly transformed input data. The input data are transformed several times and the different transformed data are applied as if they were independent inputs. The independent inputs are classified using stage neural networks and the 0utputs from the stage networks are then weighted and combined to make a decision. Experimental …
Exploiting Fine-Grain Concurrency Analytical Insights In Superscalar Processor Design, Pradeep K. Dubey, George B. Adams Iii, Michael J. Flynn
Exploiting Fine-Grain Concurrency Analytical Insights In Superscalar Processor Design, Pradeep K. Dubey, George B. Adams Iii, Michael J. Flynn
Department of Electrical and Computer Engineering Technical Reports
This dissertation develops analytical models to provide insight into various design issues associated with superscalar-type processors, i.e., the processors capable of executing multiple instructions per cycle. A survey of the existing machines and literature has been completed with a proposed classification of various approaches for exploiting fine-grain concurrency. Optimization of a single pipeline is discussed based on an analytical model. The model-predicted performance curves are found to be in close proximity to published results using simulation techniques. A model is also developed for comparing different branch strategies for single-pipeline processors in terms of their effectiveness in reducing branch delay. The …
Real-Time Helicopter Flight Control: Modelling And Control By Linearization And Neural Networks, Tobias J. Pallett, Shaheen Ahmad
Real-Time Helicopter Flight Control: Modelling And Control By Linearization And Neural Networks, Tobias J. Pallett, Shaheen Ahmad
Department of Electrical and Computer Engineering Technical Reports
In this report we determine the dynamic model of a miniature helicopter in hovering flight. Identification procedures for the nonlinear terms are also described. The model is then used to design several linearized control laws and a neural network controller. The controllers were then flight tested on a miniature helicopter flight control test bed the details of which are also presented in this report. Experimental performance of the linearized and neural network controllers are discussed. It was found from experimentation that the adaptive neural network technique was able to improve helicopter flight performance.
Blockwise Transform Image Coding Enhancement And Edge Detection, Sabzali Aghagolzadeh
Blockwise Transform Image Coding Enhancement And Edge Detection, Sabzali Aghagolzadeh
Department of Electrical and Computer Engineering Technical Reports
The goal of this thesis is high quality image coding, enhancement and edge detection. A unified approach using novel fast transforms is developed to achieve all three objectives. Requirements are low bit rate, low complexity of implementation and parallel processing. The last requirement is achieved by processing the image in small blocks such that all blocks can be processed simultaneously. This is similar to biological vision. A major issue is to minimize the resulting block effects. This is done by using proper transforms and possibly an overlap-save technique. The bit rate in image coding is minimized by developing new results …