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- Title
- Studies on Stochastic Multi-user Scheduling in Wireless Communication.
- Creator
- Wang, Di, Morgera, Salvatore D., Wang, Xin, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
We developed a cross layer design which combines retransmission diversity and multi-user diversity for wireless communication. To this end, a joint design of adaptive modulation and coding with retransmission-based automatic repeat request protocol is outlined. This design is applied to devise multi-user scheduling schemes, which can optimally capture the available multi-user and retransmission diversities. In addition, the proposed on-line scheduling algorithms can operate even when the...
Show moreWe developed a cross layer design which combines retransmission diversity and multi-user diversity for wireless communication. To this end, a joint design of adaptive modulation and coding with retransmission-based automatic repeat request protocol is outlined. This design is applied to devise multi-user scheduling schemes, which can optimally capture the available multi-user and retransmission diversities. In addition, the proposed on-line scheduling algorithms can operate even when the underl ying fading channel distribution is unknown, while asymptotically converging to the offline benchmark with guarantees on prescribed fairness and rate requirements. Numerical results are provided to verify the merits of our novel schemes for multi-user transmissions over Nakagami block fading channels.
Show less - Date Issued
- 2008
- PURL
- http://purl.flvc.org/fau/fd/FA00012568
- Subject Headings
- Stochastic processes--Data processing, Wireless communication systems, Computer network protocols, Code division multiple access, Modulation (Electronics), Signal processing--Digital techniques
- Format
- Document (PDF)
- Title
- Studies on nonlinear activity and cross-entropy considerations in neural networks.
- Creator
- Abusalah, Salahalddin Tawfiq., Florida Atlantic University, Neelakanta, Perambur S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The objectives of this research as deliberated in this dissertation are two-folded: (i) To study the nonlinear activity in the neural complex (real and artificial) and (ii) to analyze the learning processe(s) pertinent to an artificial neural network in the information-theoretic plane using cross-entropy error-metrics. The research efforts envisaged enclave the following specific tasks: (i) Obtaining a general solution for the Bernoulli-Riccati equation to represent a single parameter family...
Show moreThe objectives of this research as deliberated in this dissertation are two-folded: (i) To study the nonlinear activity in the neural complex (real and artificial) and (ii) to analyze the learning processe(s) pertinent to an artificial neural network in the information-theoretic plane using cross-entropy error-metrics. The research efforts envisaged enclave the following specific tasks: (i) Obtaining a general solution for the Bernoulli-Riccati equation to represent a single parameter family of S-shaped (sigmoidal) curves depicting the nonlinear activity in the neural network. (ii) Analysis of the logistic growth of output versus input values in the neural complex (real and artificial) under the consideration that the boundaries of the sets constituting the input and output entities are crisp and/or fuzzy. (iii) Construction of a set of cross-entropy error-metrics (known as Csiszar's measures) deduced in terms of the parameters pertinent to a perceptron topology and elucidation of their relative effectiveness in training the network optimally towards convergence. (iv) Presenting the methods of symmetrizing and balancing the aforesaid error-entropy measures (in the information-theoretic plane) so as to make them usable as error-metrics in the test domain. (v) Description and analysis of the dynamics of neural learning process in the information-theoretic plane for both crisp and fuzzy attributes of input values. Relevant to these topics portraying the studies on nonlinear activity and cross-entropy considerations vis-a-vis neural networks, newer and/or exploratory inferences are made, logical conclusions are enumerated and relative discussions are presented along with the scope for future research to be pursued.
Show less - Date Issued
- 1996
- PURL
- http://purl.flvc.org/fcla/dt/12447
- Subject Headings
- Neural networks (Computer science), Entropy (Information theory), Nonlinear control theory
- Format
- Document (PDF)
- Title
- Studies on modern telecommunications planning: Technoeconomical considerations and environmental issues.
- Creator
- Baeza, Daniel Michael., Florida Atlantic University, Neelakanta, Perambur S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The research addressed and presented in this dissertation can be placed within the broad scope of telecommunications technoeconomics. The relevant efforts include the subject-matter of identifying the issues posed by emerging technologies, related revenue considerations and environmental issues in modern telecommunications practice specific to service providers' perspectives. The topic-wise problems studied and analyzed are as follows: (1) A comprehensive portrayal of managerial concerns and...
Show moreThe research addressed and presented in this dissertation can be placed within the broad scope of telecommunications technoeconomics. The relevant efforts include the subject-matter of identifying the issues posed by emerging technologies, related revenue considerations and environmental issues in modern telecommunications practice specific to service providers' perspectives. The topic-wise problems studied and analyzed are as follows: (1) A comprehensive portrayal of managerial concerns and considerations on the technoeconomical perspectives vis-a-vis modern telecommunications; (2) Relevant analytical studies pertinent to: (1) "Greenfield starts" in a fresh, telecommunications deployment in a virgin service zone; (2) Embedded architectures; (3) Technology enhancements; (4) Environmental issues. The greenfield effort is analyzed to portray the feasibility of achieving technoeconomically optimal alternative designs. The embedded architecture refers to the prevailing infrastructure and their optimal usage is indicated via an arbitrated traffic-sharing technique. Concerning technology enhancements, "all-optical" technology is indicated as the ultimate goal. However, in the interim period, the optimal use of transitory technology such xDSL, MPLS, and others, is suggested and studied. Lastly, the environmental implications that coexist with technoeconomical impacts on modern telecommunications deployment are analyzed.
Show less - Date Issued
- 2000
- PURL
- http://purl.flvc.org/fcla/dt/12655
- Subject Headings
- Telecommunication systems--Management, Engineering economy, Telecommunication systems--Environmental aspects
- Format
- Document (PDF)
- Title
- Studies on transreceive diversity schemes (including "polarization-sense" antenna diversity) for wireless communication systems.
- Creator
- Preedalumpabut, Wichean., Florida Atlantic University, Neelakanta, Perambur S., Morgera, Salvatore D., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The research addressed in this study and deliberated in the dissertation is broadly tied to finding hybrid methods of diversity compatible for modern wireless applications. The hybrid strategy advocated thereof involves a combined use of space- (antenna and polarization), frequency-, and time-diversity schemes in a judicious manner so as to realize a desirable BER versus Eb/No performance across RF links that face multipath and other unwanted EM artifacts. The underlying reason for the hybrid...
Show moreThe research addressed in this study and deliberated in the dissertation is broadly tied to finding hybrid methods of diversity compatible for modern wireless applications. The hybrid strategy advocated thereof involves a combined use of space- (antenna and polarization), frequency-, and time-diversity schemes in a judicious manner so as to realize a desirable BER versus Eb/No performance across RF links that face multipath and other unwanted EM artifacts. The underlying reason for the hybrid scheme as above is to replace multiple-antenna based transreceive diversity. Such multiple antennas would otherwise require large base station real estate and may not be compatible for hand-held (space-constrained) RF units. On the contrary, use of hybrid schemes would restrict multiple number of antennas and conserves the space. After analyzing a set of plausible techniques of hybrid diversity compatible for modern wireless techniques, a focused study has been done on polarization-sense (PS) antenna diversity scheme. Its fruitful application for indoor systems (like Bluetooth(TM)/ZigBee(TM)) against multipath effects is demonstrated via simulation and experimental studies. Further, the PS-antenna diversity is shown to offer improved BER versus Eb/N o performance in pilot channels used in CDMA2000 systems. Also, such PS-diversity is shown to help improving the GPS receiver performance under RFI/jamming environment. The technique and heuristics proposed towards the PS-antenna diversity scheme imply novel and hitherto unexplored efforts in wireless communications. Lastly the dissertation concludes summarizing the results and offers open-questions for further studies.
Show less - Date Issued
- 2004
- PURL
- http://purl.flvc.org/fcla/dt/12104
- Subject Headings
- Wireless communication systems, Antennas (Electronics)
- Format
- Document (PDF)
- Title
- Submicron CAD design and analysis of MOS Current Mirrors.
- Creator
- Rivas-Torres, Wilfredo, Florida Atlantic University, Roth, Zvi S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Current Mirrors are widely used circuits in IC designs. They are used as current sources and loads. The proper selection of a Current Mirror configuration is therefore important. This thesis reviews critical parameters for Current Minors characterization. Six MOS Current Mirror configurations are studied, and their performance characteristics are compared. The proper selection and use of MOSFET models are presented. It is shown that CAD-based design and analysis is indispensable if realistic...
Show moreCurrent Mirrors are widely used circuits in IC designs. They are used as current sources and loads. The proper selection of a Current Mirror configuration is therefore important. This thesis reviews critical parameters for Current Minors characterization. Six MOS Current Mirror configurations are studied, and their performance characteristics are compared. The proper selection and use of MOSFET models are presented. It is shown that CAD-based design and analysis is indispensable if realistic MOS models such as BSIM3 are used. The CAD based analysis and design employs simulation parameter tuning, optimization and swept parameters. The presented CAD techniques allow a designer to make important tradeoffs for different configurations. One of the main thesis observations is that it is not always necessary to use more involved Current Mirror configurations; a Simple Current Mirror Configuration is often sufficient. The thesis also studies the adverse effects on the design caused by process variations.
Show less - Date Issued
- 2004
- PURL
- http://purl.flvc.org/fcla/dt/13119
- Subject Headings
- Metal oxide semiconductors--Computer-aided design, Integrated circuits, Metal oxide semiconductor field-effect transistors
- Format
- Document (PDF)
- Title
- Studies on carrier-free (or ultra-wideband) radar performance under clutter and stealth-target environments.
- Creator
- Mendivil, Edwin David., Florida Atlantic University, De Groff, Dolores F., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
This thesis is concerned with the use of ultra-wideband radar detection specific to the following target and background considerations. (1) Statistical attributes of the RCS models of stealth-targets illuminated by ultra-wideband radars. (2) Analysis of radar echo signatures of low flying stealth-targets with a background of sea-clutter and illuminated by an ultra-wideband radar. (3) Analysis of impulse echoes from simple (planar) surface(s) coated with a radar absorbing material (RAM). The...
Show moreThis thesis is concerned with the use of ultra-wideband radar detection specific to the following target and background considerations. (1) Statistical attributes of the RCS models of stealth-targets illuminated by ultra-wideband radars. (2) Analysis of radar echo signatures of low flying stealth-targets with a background of sea-clutter and illuminated by an ultra-wideband radar. (3) Analysis of impulse echoes from simple (planar) surface(s) coated with a radar absorbing material (RAM). The first problem refers to the elucidation of Swerling-Marcum type classifications of RCS fluctuation(s) to characterize the stochastical aspects of the echoes from stealth-targets illuminated by an impulse from an ultra-wideband radar. In the second analysis, performance of a radar receiver configuration, using the log-likelihood function of the signal received from a stealth target flying at low altitude over the sea-surface is predicted. The third effort addressed provides analytical representations in time-domain of echoes from planar surface(s) coated with RAM's for normal incidence of ultra-wideband short pulse illumination.
Show less - Date Issued
- 1996
- PURL
- http://purl.flvc.org/fcla/dt/15278
- Subject Headings
- Radar, Signal processing, Radar cross sections, Stealth aircraft
- Format
- Document (PDF)
- Title
- Structure and motion estimation from image sequences.
- Creator
- Shieh, Jen-yu., Florida Atlantic University, Zhuang, Hanqi, Sudhakar, Raghavan, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The objective of this dissertation is to develop effective algorithms for estimating the 3-D structure of a scene and its relative motion with respect to a camera or a pair of cameras from a sequence of images acquired by the cameras, under the assumption that the relative motion of the camera is small from one frame to another. This dissertation presents an approach of computing depth maps from an image sequence, which combines the direct depth estimation method with the optical flow based...
Show moreThe objective of this dissertation is to develop effective algorithms for estimating the 3-D structure of a scene and its relative motion with respect to a camera or a pair of cameras from a sequence of images acquired by the cameras, under the assumption that the relative motion of the camera is small from one frame to another. This dissertation presents an approach of computing depth maps from an image sequence, which combines the direct depth estimation method with the optical flow based method. More specifically, optical flow on and near moving edges are computed using a correlation technique. The optical flow information is then fused with the gradient information to estimate depth not only on moving edges but also in internal regions. Depth estimation is formulated as a discrete Kalman filter problem and is solved in three stages. In the prediction stage, the depth map estimated for the previous frame, together with knowledge of the camera motion, is used to predict the depth variance at each pixel in the current frame. In the estimation stage, a vector-version of Kalman filter formulation is adapted and simplified to refine the predicted depth map. The resulting estimation algorithm takes into account the information from the neighboring pixels, and thus is much more robust than the scalar-version Kalman filter implementation. In the smoothing stage, morphological filtering is applied to reduce the effect of measurement noise and fill in uncertain areas based on the error covariance information. Since the depth at each pixel is estimated locally, the algorithm presented in this paper can be implemented on a parallel computer. The performance of the presented method is assessed through simulation and experimental studies. A new approach for motion estimation from stereo image sequences is also proposed in this dissertation. First a stereo motion estimation model is derived using the direct dynamic motion estimation technique. The problem is then solved by applying a discrete Kalman filter that facilitates the use of a long stereo image sequence. Typically, major issues in such an estimation method are stereo matching, temporal matching, and noise sensitivity. In the proposed approach, owing to the use of temporal derivatives in the motion estimation model, temporal matching is not needed. The effort for stereo matching is kept to a minimum with a parallel binocular configuration. Noise smoothing is achieved by the use of a sufficiently large number of measurement points and a long sequence of stereo images. Both simulation and experimental studies have also been conducted to assess the effectiveness of the proposed approach.
Show less - Date Issued
- 1992
- PURL
- http://purl.flvc.org/fcla/dt/12320
- Subject Headings
- Three-dimensional display systems, Imaging systems, Photography, Stereoscopic, Imaging transmission
- Format
- Document (PDF)
- Title
- Stochastical aspects of neuronal activity, neural networks, and communication.
- Creator
- De Groff, Dolores F., Florida Atlantic University, Neelakanta, Perambur S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
By revisiting the popular framework of depicting neuronal (collective) activities as analogous to Ising's spin-glass theory of interacting magnetic spins, the contradictions that coexist with such an analogy are extracted and discussed. To alleviate such contradictions, an alternative strategy of equating the neuronal interactions to the partially anisotropic nematic phase of disorder pertaining to liquid crystals is proposed. Hence, the extent of anisotropy in the neuronal system, quantified...
Show moreBy revisiting the popular framework of depicting neuronal (collective) activities as analogous to Ising's spin-glass theory of interacting magnetic spins, the contradictions that coexist with such an analogy are extracted and discussed. To alleviate such contradictions, an alternative strategy of equating the neuronal interactions to the partially anisotropic nematic phase of disorder pertaining to liquid crystals is proposed. Hence, the extent of anisotropy in the neuronal system, quantified in terms of an order-function, is specified to elucidate the nonlinear squashing action of the input-output relations in a neuronal cell. The relevant approach thereof, is based on Langevin's theory considerations as applied to dipole molecules. Further, in view of the stochastical properties due to the inherent disorder associated with the neuronal assembly, the progression of state-transitions across the interconnected cells is modeled as a momentum flow relevant to particle dynamics. Hence, corresponding wave mechanics attributions of such a collective movement of state-transition activity are described in terms of a probabilistic wave function. Lastly, the stochastical aspects of noise-perturbed neuronal dynamics are studied via Fokker-Planck equation representing the Langevin-type relaxational (nonlinear) process associated with the neuronal states. On each of these topics portraying the stochastical characteristics of the neuronal assembly and its activities, newer and/or more exploratory inferences are made, logical conclusions are enumerated and relevant discussions are presented along with the scope for future research to be pursued.
Show less - Date Issued
- 1993
- PURL
- http://purl.flvc.org/fcla/dt/12326
- Subject Headings
- Neurons--Mathematical models, Stochastic processes, Neural networks (Computer science)
- Format
- Document (PDF)
- Title
- Stochastical and neuromimetic aspects of modeling electromagnetic composite materials.
- Creator
- Park, Joseph C., Florida Atlantic University, Neelakanta, Perambur S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
This dissertation is concerned primarily with the analytical modeling of a class of electromagnetic composite materials using the concepts of stochastical mixture theory, principles of electromagnetics and neuromimetic considerations. The global behavior of the test composite is ascertained in terms of the constitutive relations of the material parameters (having stochastical attributions) and the intramaterial hierarchy is modeled as massively interconnected, interacting units depicting such...
Show moreThis dissertation is concerned primarily with the analytical modeling of a class of electromagnetic composite materials using the concepts of stochastical mixture theory, principles of electromagnetics and neuromimetic considerations. The global behavior of the test composite is ascertained in terms of the constitutive relations of the material parameters (having stochastical attributions) and the intramaterial hierarchy is modeled as massively interconnected, interacting units depicting such systems as mimetics of neural networks. Pertinent research efforts enclave the following specific tasks: (i) Modeling a multi-constituent electromagnetic composite medium in terms of the characteristics of its individual constituents and their spatial (random or orderly) dispositions. (ii) Assessment of nonspherical particulate effects (in terms of the stochastical attributes) on the global response of such composite materials. (iii) Evaluation of interparticle interactions and their implicit effects on the effective electromagnetic properties of the composite media. (iv) Assaying the transitional behavior of the test composites and, (v) modeling electromagnetic composites as neuromimetics correlating their effective material characteristics to the corresponding state-transitional response of a massively interconnected neural network. Results arising from these theoretical considerations are compared with data compiled via experimental studies performed (where feasible) or otherwise correlated with theoretical and/or experimental results available elsewhere in the literature. Specific experimental efforts carried out refer to piezoelectric rubber composites and their application in controlling acoustic beamforming via electrical 'pinch off' (which mimics the inhibitory response in a neuronal cell); as well as exclusive experimental tasks to verify the transitional lossy behavior model developed presently using a set of fast-ion conductor composites and dielectric-plus-conductor mixtures. Lastly, inferential conclusions are presented and discussed with an outline on the scope of extensions to the present work.
Show less - Date Issued
- 1994
- PURL
- http://purl.flvc.org/fcla/dt/12359
- Subject Headings
- Composite materials--Electric properties, Composite materials--Magnetic properties, Stochastic processes
- Format
- Document (PDF)
- Title
- Software development for ecological data systems.
- Creator
- Lostal, Sergio L., Florida Atlantic University, Larrondo-Petrie, Maria M., Solomon, Martin K., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Software development for ecological data systems is concentrated in the description, modeling, and standardization of large amounts of ecological data. Ecological data assembled in many formats is very difficult to reuse. This thesis develops a database model that supports the storage of heterogeneous data in standardized formats. Ecological data standardization is solved with the specification of a structure conversion system. Because input formats cannot be predicted, a scientific data...
Show moreSoftware development for ecological data systems is concentrated in the description, modeling, and standardization of large amounts of ecological data. Ecological data assembled in many formats is very difficult to reuse. This thesis develops a database model that supports the storage of heterogeneous data in standardized formats. Ecological data standardization is solved with the specification of a structure conversion system. Because input formats cannot be predicted, a scientific data description language was created to control the execution of the conversion system. System analysis is based on interviews with South Florida Water Management District scientists conducting ecosystem research, and ecological data collected at Lake Okeechobee, Florida, during a five-year study. Object-oriented and structural methods were used for analysis. Development is complemented with an introduction to user interfaces.
Show less - Date Issued
- 1996
- PURL
- http://purl.flvc.org/fcla/dt/15344
- Subject Headings
- Ecology--Data processing, Information storage and retrieval systems--Ecology, Okeechobee, Lake (Fla)
- Format
- Document (PDF)
- Title
- Simulation of autonomous knowledge-based navigation in unknown two-dimensional environment with polygonal obstacles.
- Creator
- McKendrick, John DeMilly., Florida Atlantic University, Cheng, Linfu, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The problem of finding optimal paths for a robot navigating in an environment where the position of each obstacle is precisely known has received much attention in the literature, however, the majority of applications problems for a robot would require it to navigate in a completely unknown. This paper focuses on an approach to solving the problem of robot navigation in an unknown, unstructured, two-dimensional environment where the positions of the polygonal obstacles were fixed in time. Few...
Show moreThe problem of finding optimal paths for a robot navigating in an environment where the position of each obstacle is precisely known has received much attention in the literature, however, the majority of applications problems for a robot would require it to navigate in a completely unknown. This paper focuses on an approach to solving the problem of robot navigation in an unknown, unstructured, two-dimensional environment where the positions of the polygonal obstacles were fixed in time. Few studies have reported on the utilization of an expert system to govern robot motion. This study relied on a knowledge-based expert system that interacted with lower-level procedures to carry out path finding and exploration functions. The expert-system shell used was OPS5 which ran on top of Lisp.
Show less - Date Issued
- 1988
- PURL
- http://purl.flvc.org/fcla/dt/14496
- Subject Headings
- Robots--Motion, Expert systems (Computer science), Robots--Motion--Computer simulation
- Format
- Document (PDF)
- Title
- Simulation-based performance evaluation of packet-switched H.264/AVC video streaming on WCDMA networks.
- Creator
- Murillo, Carlos A., Florida Atlantic University, Iskander, Cyril-Daniel, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
This thesis presents the simulation based performance evaluation on the transmission of multimedia services (H.264/AVC video streaming) to a mobile user over a packet-switched wireless network based on the WCDMA standard. The H.264/AVC refers to the codec, which is used as the main tool for video compression. It enables the transport of high bandwidth video data over Third Generation (3G) wireless systems by offering a high video compression rate, adaptability to the channel, and error...
Show moreThis thesis presents the simulation based performance evaluation on the transmission of multimedia services (H.264/AVC video streaming) to a mobile user over a packet-switched wireless network based on the WCDMA standard. The H.264/AVC refers to the codec, which is used as the main tool for video compression. It enables the transport of high bandwidth video data over Third Generation (3G) wireless systems by offering a high video compression rate, adaptability to the channel, and error resilience. It is transported using the RTP/UDP/IP protocol stack over the 3G wireless system. The WCDMA technology is simulated with special emphasis on the upper layers of the wireless channel. The performance of the WCDMA system is studied when transporting RTP/UDP/IP packets of H.264/AVC compressed video data under diverse configuration scenarios, namely, ARQ schemes and variable length of the transmitted frame at the link layer. These components of a packet-switched streaming service are integrated into a software simulation model, which is used to evaluate the end-to-end H.264/AVC video quality in a WCDMA wireless network.
Show less - Date Issued
- 2005
- PURL
- http://purl.flvc.org/fcla/dt/13291
- Subject Headings
- Wireless communication systems, Mobile communication systems, Global system for mobile communications, Code division multiple access, Streaming technology (Telecommunications)
- Format
- Document (PDF)
- Title
- THE STEP RECOVERY DIODE WITH APPLICATIONS AS A FREQUENCY MULTIPLIER.
- Creator
- STROBEL, RUSSELL ALAN., Florida Atlantic University, Gazourian, Martin G., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Portable UHF transceivers typically require minimal current drain frequency converters to multiply the frequencies generated by crystal controlled oscillators up to the UHF band. The step recovery diode (SRD) provides an approach to frequency multiplication that requires no d.c. bias and hence minimizes battery drain. This thesis compares the SRD to the more conventional varactor and analyzes SRD device physics and characteristics. SRD operation is explained in terms of the conduction and...
Show morePortable UHF transceivers typically require minimal current drain frequency converters to multiply the frequencies generated by crystal controlled oscillators up to the UHF band. The step recovery diode (SRD) provides an approach to frequency multiplication that requires no d.c. bias and hence minimizes battery drain. This thesis compares the SRD to the more conventional varactor and analyzes SRD device physics and characteristics. SRD operation is explained in terms of the conduction and depletion intervals. The rapid transition from the conduction to the depletion mode allows the SRD to generate high order harmonics of the input frequency. A step-by-step design procedure for a series mode frequency multiplier is presented and empirical observations are used to help explain multiplier operation. The jump phenomena and hysteresis effects previously unexplained in relation to SRD multipliers are explored. Finally, it is shown that the SRD can function as a parametric amplifier.
Show less - Date Issued
- 1979
- PURL
- http://purl.flvc.org/fcla/dt/13970
- Subject Headings
- Diodes, Switching, Diodes, Semiconductor
- Format
- Document (PDF)
- Title
- Rough Set-Based Software Quality Models and Quality of Data.
- Creator
- Bullard, Lofton A., Khoshgoftaar, Taghi M., Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
In this dissertation we address two significant issues of concern. These are software quality modeling and data quality assessment. Software quality can be measured by software reliability. Reliability is often measured in terms of the time between system failures. A failure is caused by a fault which is a defect in the executable software product. The time between system failures depends both on the presence and the usage pattern of the software. Finding faulty components in the development...
Show moreIn this dissertation we address two significant issues of concern. These are software quality modeling and data quality assessment. Software quality can be measured by software reliability. Reliability is often measured in terms of the time between system failures. A failure is caused by a fault which is a defect in the executable software product. The time between system failures depends both on the presence and the usage pattern of the software. Finding faulty components in the development cycle of a software system can lead to a more reliable final system and will reduce development and maintenance costs. The issue of software quality is investigated by proposing a new approach, rule-based classification model (RBCM) that uses rough set theory to generate decision rules to predict software quality. The new model minimizes over-fitting by balancing the Type I and Type II niisclassiflcation error rates. We also propose a model selection technique for rule-based models called rulebased model selection (RBMS). The proposed rule-based model selection technique utilizes the complete and partial matching rule sets of candidate RBCMs to determine the model with the least amount of over-fitting. In the experiments that were performed, the RBCMs were effective at identifying faulty software modules, and the RBMS technique was able to identify RBCMs that minimized over-fitting. Good data quality is a critical component for building effective software quality models. We address the significance of the quality of data on the classification performance of learners by conducting a comprehensive comparative study. Several trends were observed in the experiments. Class and attribute had the greatest impact on the performance of learners when it occurred simultaneously in the data. Class noise had a significant impact on the performance of learners, while attribute noise had no impact when it occurred in less than 40% of the most significant independent attributes. Random Forest (RF100), a group of 100 decision trees, was the most, accurate and robust learner in all the experiments with noisy data.
Show less - Date Issued
- 2008
- PURL
- http://purl.flvc.org/fau/fd/FA00012567
- Subject Headings
- Computer software--Quality control, Computer software--Reliability, Software engineering, Computer arithmetic
- Format
- Document (PDF)
- Title
- Using adaptive controllers in the realization of a position control scheme.
- Creator
- Samples, Robert Hyram, Jr., Florida Atlantic University, Pajunen, Grazyna, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Many positioning systems with varying loads or geometries, such as robotic systems, could take advantage of the class of non-linear controllers known as Adaptive Controls. Model Reference and Pole Placement Adaptive Controllers are usually the preferred techniques for position control systems. Pole Placement is the more universally applicable technique. Adaptive controllers must be able to change control parameters as the system's parameters change (i.e., as is the case with a load or...
Show moreMany positioning systems with varying loads or geometries, such as robotic systems, could take advantage of the class of non-linear controllers known as Adaptive Controls. Model Reference and Pole Placement Adaptive Controllers are usually the preferred techniques for position control systems. Pole Placement is the more universally applicable technique. Adaptive controllers must be able to change control parameters as the system's parameters change (i.e., as is the case with a load or geometry change). The most common and perhaps the fastest converging technique uses the Least Squares Identification Algorithm. Many positioning systems cannot tolerate overshoot. These systems should use an adaptive velocity controller in conjunction with a conventional position controller. This will minimize system overshoot during the learning period. Adaptive controllers tend to be very complex and require a great number of computations. With today's advances in computer technology, adaptive controllers can now be economically considered for many industrial, consumer and military positioning applications.
Show less - Date Issued
- 1988
- PURL
- http://purl.flvc.org/fcla/dt/14474
- Subject Headings
- Adaptive control systems
- Format
- Document (PDF)
- Title
- Synthesis of vision-based robot calibration using moving cameras.
- Creator
- Wang, Kuanchih., Florida Atlantic University, Roth, Zvi S., Zhuang, Hanqi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
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Robot calibration using a vision system and moving cameras is the focus of this dissertation. The dissertation contributes in the areas of robot modeling, kinematic identification and calibration measurement. The effects of perspective distortion of circular camera calibration points is analyzed. A new modified complete and parametrically continuous robot kinematic model, an evolution of the complete and parametrically continuous (CPC) model, is proposed. It is shown that the model's error...
Show moreRobot calibration using a vision system and moving cameras is the focus of this dissertation. The dissertation contributes in the areas of robot modeling, kinematic identification and calibration measurement. The effects of perspective distortion of circular camera calibration points is analyzed. A new modified complete and parametrically continuous robot kinematic model, an evolution of the complete and parametrically continuous (CPC) model, is proposed. It is shown that the model's error-model can be developed easily as the structure of this new model is very simple and similar to the Denavit-Hartenbert model. The derivation procedure of the error-model follows a systematic method that can be applied to any kind of robot arms. Pose measurement is the most crucial step in robot calibration. The use of stereo as well as mono mobile camera measurement system for collection of pose data of the robot end-effector is investigated. The Simulated Annealing technique is applied to the problem of optimal measurement configuration selection. Joint travel limits can be included in the cost function. It is shown that trapping into local minimum points can be effectively avoided by properly choosing an initial point and a temperature schedule. The concept of simultaneous calibration of camera and robot is developed and implemented as an automated process that determines the system model parameters using only the system's internal sensors. This process uses a unified mathematical model for the entire robot/camera system. The results of the kinematic identification, optimal configuration selection, and simultaneous calibration of robot and camera using the PUMA 560 robot arm have demonstrated that the modified complete and parametrically continuous model is a viable and simple modeling tool, which can achieve desired accuracy. The systematic way of modeling and performing of different kinds of vision-based robot applications demonstrated in this dissertation will pave the way for industrial standardizing of robot calibration done by the robot user on the manufacturing floor.
Show less - Date Issued
- 1993
- PURL
- http://purl.flvc.org/fcla/dt/12339
- Subject Headings
- Robot vision, Robot cameras--Calibration
- Format
- Document (PDF)
- Title
- DEEP LEARNING REGRESSION MODELS FOR LIMITED BIOMEDICAL TIME-SERIES DATA.
- Creator
- Hssayeni, Murtadha D., Behnaz Ghoraani, Behnaz, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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Time-series data in biomedical applications are gaining an increased interest to detect and predict underlying diseases and estimate their severity, such as Parkinson’s disease (PD) and cardiovascular diseases. This interest is driven by advances in wearable sensors and deep learning models to a large extent. In the literature, less attention has been paid to regression models for continuous outcomes in these applications, especially when dealing with limited data. Training deep learning...
Show moreTime-series data in biomedical applications are gaining an increased interest to detect and predict underlying diseases and estimate their severity, such as Parkinson’s disease (PD) and cardiovascular diseases. This interest is driven by advances in wearable sensors and deep learning models to a large extent. In the literature, less attention has been paid to regression models for continuous outcomes in these applications, especially when dealing with limited data. Training deep learning models on raw limited data results in overfitted models, which is the main technical challenge we address in this dissertation. An example of limited and\or imbalanced time-series data is PD’s motion signals that are needed for the continuous severity estimation of Parkinson’s disease (PD). The significance of this continuous estimation is providing a tool for longitudinal monitoring of daily motor and non-motor fluctuations and managing PD medications. The dissertation objective is to train generalizable deep learning models for biomedical regression problems when dealing with limited training time-series data. The goal is designing, developing, and validating an automatic assessment system based on wearable sensors that can measure the severity of PD complications in the home-living environment while patients with PD perform their activities of daily living (ADL). We first propose using a combination of domain-specific feature engineering, transfer learning, and an ensemble of multiple modalities. Second, we utilize generative adversarial networks (GAN) and propose a new formulation of conditional GAN (cGAN) as a generative model for regression to handle an imbalanced training dataset. Next, we propose a dual-channel auxiliary regressor GAN (AR-GAN) trained using Wasserstein-MSE-correlation loss. The proposed AR-GAN is used as a data augmentation method in regression problems.
Show less - Date Issued
- 2022
- PURL
- http://purl.flvc.org/fau/fd/FA00013992
- Subject Headings
- Deep learning (Machine learning), Regression analysis--Mathematical models, Biomedical engineering
- Format
- Document (PDF)
- Title
- SELECTED APPLICATIONS OF MPC.
- Creator
- Ghaseminejad, Mohammad Raeini, Liu, Feng-Hao, Nojoumian, Mehrdad, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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Secure multiparty computation (secure MPC) is a computational paradigm that enables a group of parties to evaluate a public function on their private data without revealing the data (i.e., by preserving the privacy of their data). This computational approach, sometimes also referred to as secure function evaluation (SFE) and privacy-preserving computation, has attracted significant attention in the last couple of decades. It has been studied in different application domains, including in...
Show moreSecure multiparty computation (secure MPC) is a computational paradigm that enables a group of parties to evaluate a public function on their private data without revealing the data (i.e., by preserving the privacy of their data). This computational approach, sometimes also referred to as secure function evaluation (SFE) and privacy-preserving computation, has attracted significant attention in the last couple of decades. It has been studied in different application domains, including in privacy-preserving data mining and machine learning, secure signal processing, secure genome analysis, sealed-bid auctions, etc. There are different approaches for realizing secure MPC. Some commonly used approaches include secret sharing schemes, Yao's garbled circuits, and homomorphic encryption techniques. The main focus of this dissertation is to further investigate secure multiparty computation as an appealing area of research and to study its applications in different domains. We specifically focus on secure multiparty computation based on secret sharing and fully homomorphic encryption (FHE) schemes. We review the important theoretical foundations of these approaches and provide some novel applications for each of them. For the fully homomorphic encryption (FHE) part, we mainly focus on FHE schemes based on the LWE problem [142] or RLWE problem [109]. Particularly, we provide a C++ implementation for the ring variant of a third generation FHE scheme called the approximate eigenvector method (a.k.a., the GSW scheme) [67]. We then propose some novel approaches for homomorphic evaluation of common functionalities based on the implemented (R)LWE [142] and [109] and RGSW [38,58] schemes. We specifically present some constructions for homomorphic computation of pseudorandom functions (PRFs). For secure computation based on secret sharing [150], we provide some novel protocols for secure trust evaluation (STE). Our proposed STE techniques [137] enable the parties in trust and reputation systems (TRS) to securely assess their trust values in each other while they keep their input trust values private. It is worth mentioning that trust and reputation are social mechanisms which can be considered as soft security measures that complement hard security measures (e.g., cryptographic and secure multiparty computation techniques) [138, 171].
Show less - Date Issued
- 2022
- PURL
- http://purl.flvc.org/fau/fd/FA00014018
- Subject Headings
- Data encryption (Computer science), Computers, privacy and data protection, Computer security
- Format
- Document (PDF)
- Title
- MACHINE LEARNING METHODS FOR IMAGE ENHANCEMENT IN DEGRADED VISUAL ENVIRONMENTS.
- Creator
- Estrada, Dennis, Tang, Yufei, Ouyang, Bing, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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Significant reduction in space, weight, power, and cost (SWAP-C) of imaging hardware has induced a paradigm shift in remote sensing where unmanned platforms have become the mainstay. However, mitigating the degraded visual environment (DVE) remains an issue. DVEs can cause a loss of contrast and image detail due to particle scattering and distortion due to turbulence-induced effects. The problem is especially challenging when imaging from unmanned platforms such as autonomous underwater...
Show moreSignificant reduction in space, weight, power, and cost (SWAP-C) of imaging hardware has induced a paradigm shift in remote sensing where unmanned platforms have become the mainstay. However, mitigating the degraded visual environment (DVE) remains an issue. DVEs can cause a loss of contrast and image detail due to particle scattering and distortion due to turbulence-induced effects. The problem is especially challenging when imaging from unmanned platforms such as autonomous underwater vehicles (AUV) and unmanned ariel vehicles (UAV). While single-frame image restoration techniques have been studied extensively in recent years, single image capture is not adequate to address the effects of DVEs due to under-sampling, low dynamic range, and chromatic aberration. Significant development has been made to employ multi-frame image fusion techniques to take advantage of spatial and temporal information to aid in the recovery of corrupted image detail and high-frequency content and increasing dynamic range.
Show less - Date Issued
- 2022
- PURL
- http://purl.flvc.org/fau/fd/FA00013987
- Subject Headings
- Image Enhancement, Machine learning, Remote sensing
- Format
- Document (PDF)
- Title
- MODELING, PATH PLANNING, AND CONTROL CO-DESIGN OF MARINE CURRENT TURBINES.
- Creator
- Hasankhani, Arezoo, Tang, Yufei, VanZwieten, James, Florida Atlantic University, Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
- Abstract/Description
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Marine and hydrokinetic (MHK) energy systems, including marine current turbines and wave energy converters, could contribute significantly to reducing reliance on fossil fuels and improving energy security while accelerating progress in the blue economy. However, technologies to capture them are nascent in development due to several technical and economic challenges. For example, for capturing ocean flows, the fluid velocity is low but density is high, resulting in early boundary layer...
Show moreMarine and hydrokinetic (MHK) energy systems, including marine current turbines and wave energy converters, could contribute significantly to reducing reliance on fossil fuels and improving energy security while accelerating progress in the blue economy. However, technologies to capture them are nascent in development due to several technical and economic challenges. For example, for capturing ocean flows, the fluid velocity is low but density is high, resulting in early boundary layer separation and high torque. This dissertation addresses critical challenges in modeling, optimization, and control co-design of MHK energy systems, with specific case studies of a variable buoyancy-controlled marine current turbine (MCT). Specifically, this dissertation presents (a) comprehensive dynamic modeling of the MCT, where data recorded by an acoustic Doppler current profiler will be used as the real ocean environment; (b) vertical path planning of the MCT, where the problem is formulated as a novel spatial-temporal optimization problem to maximize the total harvested power of the system in an uncertain oceanic environment; (c) control co-design of the MCT, where the physical device geometry and turbine path control are optimized simultaneously. In a nutshell, the contributions are summarized as follows:
Show less - Date Issued
- 2022
- PURL
- http://purl.flvc.org/fau/fd/FA00013991
- Subject Headings
- Marine turbines, Modeling dynamic systems, Ocean wave power
- Format
- Document (PDF)
