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Articles 1 - 17 of 17
Full-Text Articles in Engineering
Analysis Of Baseband Equivalent Noise In A First-Order Correlation Loop Utilizing Filtered Pseudonoise Signals, Kurt Louis Kosbar, Christopher J. Scholten
Analysis Of Baseband Equivalent Noise In A First-Order Correlation Loop Utilizing Filtered Pseudonoise Signals, Kurt Louis Kosbar, Christopher J. Scholten
Electrical and Computer Engineering Faculty Research & Creative Works
Conventional direct-sequence and frequency-hopping spread spectrum systems utilize delay-lock loops to track the timing epoch of pseudonoise codes. These devices perform admirably at high signal-to-noise ratios (SNR), however, they are suboptimal at moderate and low SNR. A correlation loop that employs appropriately filtered pseudonoise signals for the local cross-correlation waveform may have superior performance under these conditions. The performance of this modified correlation loop will be determined by the cross correlation function of the transmitted waveform and locally generated reference signals, along with the statistics of the baseband equivalent noise process. In this work, we find the statistics of the …
Noise Generators For The Simulation Of Digital Communication Systems, Martina F. Schollmeyer, William H. Tranter
Noise Generators For The Simulation Of Digital Communication Systems, Martina F. Schollmeyer, William H. Tranter
Electrical and Computer Engineering Faculty Research & Creative Works
The generation of random numbers, having uniform and Gaussian distributions, with application to the time-domain simulation of communication systems is considered. The specific goal is to identify appropriate noise generation algorithms for use in system simulations for the determination of the symbol error probability of a digital communication system. Several methods of generating both uniform and Gaussian random numbers are examined. The algorithms considered were taken from those discussed in recent literature that appeared most appropriate for our problem. The algorithms were programmed in FORTRAN for use on a PC with math-coprocessor. Tests to evaluate the statistical properties of the …
An Architecture Level Simulation Methodology, Paul D. Stigall, Ram Huggahalli
An Architecture Level Simulation Methodology, Paul D. Stigall, Ram Huggahalli
Electrical and Computer Engineering Faculty Research & Creative Works
Using the Architecture Design and Assessment System (ADAS), the Processor Level Architecture of an Example Computer System is First Represented as a Directed Graph. Then, a Method of Simulating Instruction Execution as a Sequence of Data Transfers between the Nodes of the Graph is Presented. the Simulation Methodology Provides Flexibility in Observing the Architecture Dynamically at the Processor Level. an Example Application for Functional Verification is Discussed. Development of Techniques to Convert Programs into Node Sequences And, to Assign Appropriate Delays to the Nodes is Necessary to Further Enhance the Applicability of the Methodology. Functional Verification and Performance Estimation through …
Quantum Network Theory Of Transport With Application To The Generalized Aharonov-Bohm Effect In Metals And Semiconductors, Cheng-Hsiao Wu, Gunter Mahler
Quantum Network Theory Of Transport With Application To The Generalized Aharonov-Bohm Effect In Metals And Semiconductors, Cheng-Hsiao Wu, Gunter Mahler
Electrical and Computer Engineering Faculty Research & Creative Works
Quantum transport for resistor networks is developed with a general form factor, where each node point of the network is associated with a potential. The phase factor of the wave function in between two adjacent nodes is related to the reflection coefficient along that path. The exact transmission probability for a generalized Aharonov-Bohm ring is derived for a clean and cold crystal ring of arbitrary two-lead connections. The even- and odd-numbered rings have distinctly different transmission behaviors. The periodicity of the odd-numbered ring with respect to the threaded magnetic flux is shown to be double to that of an even-numbered …
The Synthesis Of Patterns Using A Series-Fed Array Of Annular Sector Radiating Line (Anserlin) Elements: Low-Profile, Circularly Polarized Radiators, James L. Drewniak, P. E. Mayes
The Synthesis Of Patterns Using A Series-Fed Array Of Annular Sector Radiating Line (Anserlin) Elements: Low-Profile, Circularly Polarized Radiators, James L. Drewniak, P. E. Mayes
Electrical and Computer Engineering Faculty Research & Creative Works
A series-fed, circularly polarized array of annular sector radiating-line elements that operates over a ground plane and has a low profile is presented. Pattern shaping can be achieved through control of the fraction of the incident power that is radiated by each element. This can be accomplished over a wide range by a simple adjustment in the geometry of each element. A synthesis technique is given, and experimental results are presented. The array is demonstrated to have a high return loss (good impedance match) and a low axial ratio
Linear Interpolation Lattice, Cameron K. Coursey, John A. Stuller
Linear Interpolation Lattice, Cameron K. Coursey, John A. Stuller
Electrical and Computer Engineering Faculty Research & Creative Works
The Well-Known Analysis and Synthesis Filters of Linear Prediction Theory Are Extended Here to Include Linear Interpolation. © 1991 IEEE
An Optoelectronic Adaptive Resonance Unit, Donald C. Wunsch, T. P. Caudell, R. A. Falk, C. David Capps
An Optoelectronic Adaptive Resonance Unit, Donald C. Wunsch, T. P. Caudell, R. A. Falk, C. David Capps
Electrical and Computer Engineering Faculty Research & Creative Works
The authors demonstrate a hardware implementation of the adaptive resonance theory ART 1 neural network architecture. The optoelectronic ART1 unit, is a novel application of an old device. This device-the 4-f or Van der Lugt correlator-has historically been used as a fast pattern classifier. Usually the correlation operation is employed as a matched filter, so that a maximum correlation peak corresponds to a well-matched pattern. The device described also uses the large peaks, but takes specific advantage of the fact that a zero-shift correlation is mathematically equivalent to a two-dimensional inner product. The authors describe a promising method for emulating …
Adaptive Gain Control And Contrast Improvement For Medical Diagnostic Ultrasound B-Mode Imaging System Using Charge-Couples Devices, Alan W. Bryant, Thomas J. Herrick
Adaptive Gain Control And Contrast Improvement For Medical Diagnostic Ultrasound B-Mode Imaging System Using Charge-Couples Devices, Alan W. Bryant, Thomas J. Herrick
Electrical and Computer Engineering Faculty Research & Creative Works
A B-mode ultrasound imaging system operates by transmitting a high-frequency sound pulse and measuring the strength and time of flight of the reflected signal. The ultrasound signal may be attenuated as much as 60 dB in its round trip to a target and must be normalized so that contrast is not lost in the far field. Manual controls for adjusting receiver gain versus depth are common in many clinical uses but are impractical in most surgical applications. The goal of this project was to design a circuit to automatically adjust the gain. A two-dimensional low-pass filter is used to approximate …
Design Of Robust Controllers For Gas Turbine Engines, D. E. Moellenhoff, Vittal S. Rao, C. A. Skarvan
Design Of Robust Controllers For Gas Turbine Engines, D. E. Moellenhoff, Vittal S. Rao, C. A. Skarvan
Electrical and Computer Engineering Faculty Research & Creative Works
This paper describes robust controller design methodologies for gas turbine engines. A linear state variable model for the engine is derived using partial derivatives. The Linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) and the Parameter Robust Linear Quadratic Gaussian (PRLQG) robust controller design methodologies have been used to design a controller for gas turbine engines. A new method is proposed by combining the features of LQG/LTR and PRLQG methods and yields good robustness properties with respect to both unstructured uncertainties in the frequency domain and structured parameter variations in the time domain. The new procedure is illustrated with the …
An Industrial Application To Neural Networks To Reusable Design, Donald C. Wunsch, R. Escobedo, T. P. Caudell, S. D. G. Smith, G. C. Johnson
An Industrial Application To Neural Networks To Reusable Design, Donald C. Wunsch, R. Escobedo, T. P. Caudell, S. D. G. Smith, G. C. Johnson
Electrical and Computer Engineering Faculty Research & Creative Works
Summary form only given, as follows. The feasibility of training an adaptive resonance theory (ART-1) network to first cluster aircraft parts into families, and then to recall the most similar family when presented a new part has been demonstrated, ART-1 networks were used to adaptively group similar input vectors. The inputs to the network were generated directly from computer-aided designs of the parts and consist of binary vectors which represent bit maps of the features of the parts. This application, referred to as group technology, is of large practical value to industry, making it possible to avoid duplication of design …
Applying Artificial Intelligence To The Identification Of Variegated Coloring In Skin Tumors, Scott E. Umbaugh, Randy Hays Moss, William V. Stoecker
Applying Artificial Intelligence To The Identification Of Variegated Coloring In Skin Tumors, Scott E. Umbaugh, Randy Hays Moss, William V. Stoecker
Electrical and Computer Engineering Faculty Research & Creative Works
The importance of color information for the automatic diagnosis of skin tumors by computer vision is demonstrated. The utility of the relative color concept is proved by the results in identifying variegated coloring. A feature file paradigm is shown to provide an effective methodology for the independent development of software modules for expert system/computer vision research. An automatic induction tool is used effectively to generate rules for identifying variegated coloring. Variegated coloring can be identified at rates as high as 92% when using the automatic induction technique in conjunction with the color segmentation method
Occupation Dynamics Of Trap States In An A-Si:H Thin-Film Transistor, J. N. Bullock, Cheng-Hsiao Wu
Occupation Dynamics Of Trap States In An A-Si:H Thin-Film Transistor, J. N. Bullock, Cheng-Hsiao Wu
Electrical and Computer Engineering Faculty Research & Creative Works
We calculate the dynamical behavior of a-Si:H thin-film transistors with an emphasis on the occupation dynamics of trap states. The appropriate rate equation for the occupation function of trap states is included. We show the relations of filling the trap states with the switch-on time and of emptying the trap charges with the switch-off time. The occupation functions in both cases are non-Fermi distribution. The quasi-equilibrium approximation underestimates those two time constants. Thus, transit time theory cannot describe the speeds of transistors made from disordered materials.
A Commodity Trading Model Based On A Neural Network-Expert System Hybrid, K. Bergerson, Donald C. Wunsch
A Commodity Trading Model Based On A Neural Network-Expert System Hybrid, K. Bergerson, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
Demonstrates a system that combines a neural network approach with an expert system to provide superior performance compared to either approach alone. Learning capability is provided in a software-based approach to commodity trading systems. The authors used the backpropagation network with some parameters selected experimentally. They used a human expert to implicitly define patterns, using hindsight, that an intelligent system might have been able to use for an accurate prediction. Desired outputs were found by a combination of observing the behavior of technical indices that normally precede a certain kind of market behavior, and by observing the actual market behavior …
Security Assessment Using Neural Computing, Badrul H. Chowdhury, B. M. Wilamowski
Security Assessment Using Neural Computing, Badrul H. Chowdhury, B. M. Wilamowski
Electrical and Computer Engineering Faculty Research & Creative Works
The advantage of fast computation capability of an artificial neural network (ANN) is used to introduce an iterative scheme for security assessment of power systems. Two related approaches are shown which demonstratedly work satisfactorily. The idea of feedback in a single-layer feedforward neural network is experimented yielding higher accuracy. The ANN is trained by using a set of data obtained from off-line analysis of the power network. After training, an approximate solution for a given condition may be found almost immediately. The approximate solution obtained is judged adequate for assessing the security of the power system. A case study is …
A Hybrid Optoelectronic Art-1 Neural Processor, Donald C. Wunsch, T. P. Caudell
A Hybrid Optoelectronic Art-1 Neural Processor, Donald C. Wunsch, T. P. Caudell
Electrical and Computer Engineering Faculty Research & Creative Works
Summary form only given. A new implementation of ART-1 (adaptive resonance theory) has been proposed that efficiently combines optical and electronic devices. All parallel computations are performed by the optics, while serial operations are performed in electronics.
A Laboratory Investigation Of Electro-Optic Kerr Effect For Detection Of Electric Transmission Line Faults, Badrul H. Chowdhury, E. Grigsby, T. J. Englert
A Laboratory Investigation Of Electro-Optic Kerr Effect For Detection Of Electric Transmission Line Faults, Badrul H. Chowdhury, E. Grigsby, T. J. Englert
Electrical and Computer Engineering Faculty Research & Creative Works
A prototype Kerr cell has been constructed and tested for detecting and identifying faults by monitoring high voltages such as are found in electric power delivery systems. Simulated faults were generated under laboratory conditions and monitored by the Kerr cell. Preliminary analysis was done using analog-to-digital conversion of the detected waveforms with a single board microprocessor serially interfaced with a personal computer. The occurrence of faults is readily observed and results indicate that identification of fault types can be accomplished within less than one cycle of a standard sixty-cycle-per-second delivery system. With a dedicated analysis system such a technique may …
A Neural Architecture For Unsupervised Learning With Shift, Scale And Rotation Invariance, Efficient Software Simulation Heuristics, And Optoelectronic Implementation, Donald C. Wunsch, D. S. Newman, T. P. Caudell, R. A. Falk, C. David Capps
A Neural Architecture For Unsupervised Learning With Shift, Scale And Rotation Invariance, Efficient Software Simulation Heuristics, And Optoelectronic Implementation, Donald C. Wunsch, D. S. Newman, T. P. Caudell, R. A. Falk, C. David Capps
Electrical and Computer Engineering Faculty Research & Creative Works
A simple modification of the adaptive resonance theory (ART) neural network allows shift, scale and rotation invariant learning. The authors point out that this can be accomplished as a neural architecture by modifying the standard ART with hardwired interconnects that perform a Fourier-Mellin transform, and show how to modify the heuristics for efficient simulation of ART architectures to accomplish the additional innovation. Finally, they discuss the implementation of this in optoelectronic hardware, using a modification of the Van der Lugt optical correlator