View All Items

Title: Distributed Extremum Seeking and Cooperative Control for Mobile Cooperative Communication Systems.
Creator: Alabri, Said, Qu, Zhihua, Wei, Lei, Vosoughi, Azadeh, Atia, George, University of Central Florida
Abstract / Description: In this thesis, a distributed extremum seeking and cooperative control algorithm is designed for mobile agents to dispersethemselves optimally in maintaining communication quality and maximizing their coverage. The networked mobile agentslocally form a virtual multiple-input multiple-output (MIMO) communication system, and they cooperatively communicateamong them by using the decode and forward cooperative communication technique. The outage probability is usedas the measure of communication...
Show moreIn this thesis, a distributed extremum seeking and cooperative control algorithm is designed for mobile agents to dispersethemselves optimally in maintaining communication quality and maximizing their coverage. The networked mobile agentslocally form a virtual multiple-input multiple-output (MIMO) communication system, and they cooperatively communicateamong them by using the decode and forward cooperative communication technique. The outage probability is usedas the measure of communication quality, and it can be estimated real-time. A general performance index balancing outageprobability and spatial dispersion is chosen for the overall system. The extremum seeking control approachis used to estimate and optimize the value of the performance index, and the cooperative formation control is applied tomove the mobile agents to achieve the optimal solution by using only the locally-available information. Through theintegration of cooperative communication and cooperative control, network connectivity and coverage of the mobile agentsare much improved when compared to either non-cooperative communication approaches or other existing control results.Analytical analysis is carried out to demonstrate the performance and robustness of the proposal methodology, andsimulation is done to illustrate its effectiveness.
Show less
Date Issued: 2013
Identifier: CFE0005082, ucf:50744
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005082

Title: Compressive Sensing and Recovery of Structured Sparse Signals.
Creator: Shahrasbi, Behzad, Rahnavard, Nazanin, Vosoughi, Azadeh, Wei, Lei, Atia, George, Pensky, Marianna, University of Central Florida
Abstract / Description: In the recent years, numerous disciplines including telecommunications, medical imaging, computational biology, and neuroscience benefited from increasing applications of high dimensional datasets. This calls for efficient ways of data capturing and data processing. Compressive sensing (CS), which is introduced as an efficient sampling (data capturing) method, is addressing this need. It is well-known that the signals, which belong to an ambient high-dimensional space, have much smaller...
Show moreIn the recent years, numerous disciplines including telecommunications, medical imaging, computational biology, and neuroscience benefited from increasing applications of high dimensional datasets. This calls for efficient ways of data capturing and data processing. Compressive sensing (CS), which is introduced as an efficient sampling (data capturing) method, is addressing this need. It is well-known that the signals, which belong to an ambient high-dimensional space, have much smaller dimensionality in an appropriate domain. CS taps into this principle and dramatically reduces the number of samples that is required to be captured to avoid any distortion in the information content of the data. This reduction in the required number of samples enables many new applications that were previously infeasible using classical sampling techniques.Most CS-based approaches take advantage of the inherent low-dimensionality in many datasets. They try to determine a sparse representation of the data, in an appropriately chosen basis using only a few significant elements. These approaches make no extra assumptions regarding possible relationships among the significant elements of that basis. In this dissertation, different ways of incorporating the knowledge about such relationships are integrated into the data sampling and the processing schemes.We first consider the recovery of temporally correlated sparse signals and show that using the time correlation model. The recovery performance can be significantly improved. Next, we modify the sampling process of sparse signals to incorporate the signal structure in a more efficient way. In the image processing application, we show that exploiting the structure information in both signal sampling and signal recovery improves the efficiency of the algorithm. In addition, we show that region-of-interest information can be included in the CS sampling and recovery steps to provide a much better quality for the region-of-interest area compared the rest of the image or video. In spectrum sensing applications, CS can dramatically improve the sensing efficiency by facilitating the coordination among spectrum sensors. A cluster-based spectrum sensing with coordination among spectrum sensors is proposed for geographically disperse cognitive radio networks. Further, CS has been exploited in this problem for simultaneous sensing and localization. Having access to this information dramatically facilitates the implementation of advanced communication technologies as required by 5G communication networks.
Show less
Date Issued: 2015
Identifier: CFE0006392, ucf:51509
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006392

Title: On Distributed Estimation for Resource Constrained Wireless Sensor Networks.
Creator: Sani, Alireza, Vosoughi, Azadeh, Rahnavard, Nazanin, Wei, Lei, Atia, George, Chatterjee, Mainak, University of Central Florida
Abstract / Description: We study Distributed Estimation (DES) problem, where several agents observe a noisy version of an underlying unknown physical phenomena (which is not directly observable), and transmit a compressed version of their observations to a Fusion Center (FC), where collective data is fused to reconstruct the unknown. One of the most important applications of Wireless Sensor Networks (WSNs) is performing DES in a field to estimate an unknown signal source. In a WSN battery powered geographically...
Show moreWe study Distributed Estimation (DES) problem, where several agents observe a noisy version of an underlying unknown physical phenomena (which is not directly observable), and transmit a compressed version of their observations to a Fusion Center (FC), where collective data is fused to reconstruct the unknown. One of the most important applications of Wireless Sensor Networks (WSNs) is performing DES in a field to estimate an unknown signal source. In a WSN battery powered geographically distributed tiny sensors are tasked with collecting data from the field. Each sensor locally processes its noisy observation (local processing can include compression,dimension reduction, quantization, etc) and transmits the processed observation over communication channels to the FC, where the received data is used to form a global estimate of the unknown source such that the Mean Square Error (MSE) of the DES is minimized. The accuracy of DES depends on many factors such as intensity of observation noises in sensors, quantization errors in sensors, available power and bandwidth of the network, quality of communication channels between sensors and the FC, and the choice of fusion rule in the FC. Taking into account all of these contributing factors and implementing a DES system which minimizes the MSE and satisfies all constraints is a challenging task. In order to probe into different aspects of this challenging task we identify and formulate the following three problems and address them accordingly:1- Consider an inhomogeneous WSN where the sensors' observations is modeled linear with additive Gaussian noise. The communication channels between sensors and FC are orthogonal power and bandwidth-constrained erroneous wireless fading channels. The unknown to be estimated is a Gaussian vector. Sensors employ uniform multi-bit quantizers and BPSK modulation. Given this setup, we ask: what is the best fusion rule in the FC? what is the best transmit power and quantization rate (measured in bits per sensor) allocation schemes that minimize the MSE? In order to answer these questions, we derive some upper bounds on global MSE and through minimizing those bounds, we propose various resource allocation schemes for the problem, through which we investigate the effect of contributing factors on the MSE.2- Consider an inhomogeneous WSN with an FC which is tasked with estimating a scalar Gaussian unknown. The sensors are equipped with uniform multi-bit quantizers and the communication channels are modeled as Binary Symmetric Channels (BSC). In contrast to former problem the sensors experience independent multiplicative noises (in addition to additive noise). The natural question in this scenario is: how does multiplicative noise affect the DES system performance? how does it affect the resource allocation for sensors, with respect to the case where there is no multiplicative noise? We propose a linear fusion rule in the FC and derive the associated MSE in closed-form. We propose several rate allocation schemes with different levels of complexity which minimize the MSE. Implementing the proposed schemes lets us study the effect of multiplicative noise on DES system performance and its dynamics. We also derive Bayesian Cramer-Rao Lower Bound (BCRLB) and compare the MSE performance of our porposed methods against the bound.As a dual problem we also answer the question: what is the minimum required bandwidth of thenetwork to satisfy a predetermined target MSE?3- Assuming the framework of Bayesian DES of a Gaussian unknown with additive and multiplicative Gaussian noises involved, we answer the following question: Can multiplicative noise improve the DES performance in any case/scenario? the answer is yes, and we call the phenomena as 'enhancement mode' of multiplicative noise. Through deriving different lower bounds, such as BCRLB,Weiss-Weinstein Bound (WWB), Hybrid CRLB (HCRLB), Nayak Bound (NB), Yatarcos Bound (YB) on MSE, we identify and characterize the scenarios that the enhancement happens. We investigate two situations where variance of multiplicative noise is known and unknown. Wealso compare the performance of well-known estimators with the derived bounds, to ensure practicability of the mentioned enhancement modes.
Show less
Date Issued: 2017
Identifier: CFE0006913, ucf:51698
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006913

Title: Applied Advanced Error Control Coding for General Purpose Representation and Association Machine Systems.
Creator: Dai, Bowen, Wei, Lei, Lin, Mingjie, Rahnavard, Nazanin, Turgut, Damla, Sun, Qiyu, University of Central Florida
Abstract / Description: General-Purpose Representation and Association Machine (GPRAM) is proposed to be focusing on computations in terms of variation and flexibility, rather than precision and speed. GPRAM system has a vague representation and has no predefined tasks. With several important lessons learned from error control coding, neuroscience and human visual system, we investigate several types of error control codes, including Hamming code and Low-Density Parity Check (LDPC) codes, and extend them to...
Show moreGeneral-Purpose Representation and Association Machine (GPRAM) is proposed to be focusing on computations in terms of variation and flexibility, rather than precision and speed. GPRAM system has a vague representation and has no predefined tasks. With several important lessons learned from error control coding, neuroscience and human visual system, we investigate several types of error control codes, including Hamming code and Low-Density Parity Check (LDPC) codes, and extend them to different directions.While in error control codes, solely XOR logic gate is used to connect different nodes. Inspired by bio-systems and Turbo codes, we suggest and study non-linear codes with expanded operations, such as codes including AND and OR gates which raises the problem of prior-probabilities mismatching. Prior discussions about critical challenges in designing codes and iterative decoding for non-equiprobable symbols may pave the way for a more comprehensive understanding of bio-signal processing. The limitation of XOR operation in iterative decoding with non-equiprobable symbols is described and can be potentially resolved by applying quasi-XOR operation and intermediate transformation layer. Constructing codes for non-equiprobable symbols with the former approach cannot satisfyingly perform with regarding to error correction capability. Probabilistic messages for sum-product algorithm using XOR, AND, and OR operations with non-equiprobable symbols are further computed. The primary motivation for the constructing codes is to establish the GPRAM system rather than to conduct error control coding per se. The GPRAM system is fundamentally developed by applying various operations with substantial over-complete basis. This system is capable of continuously achieving better and simpler approximations for complex tasks.The approaches of decoding LDPC codes with non-equiprobable binary symbols are discussed due to the aforementioned prior-probabilities mismatching problem. The traditional Tanner graph should be modified because of the distinction of message passing to information bits and to parity check bits from check nodes. In other words, the message passing along two directions are identical in conventional Tanner graph, while the message along the forward direction and backward direction are different in our case. A method of optimizing signal constellation is described, which is able to maximize the channel mutual information.A simple Image Processing Unit (IPU) structure is proposed for GPRAM system, to which images are inputted. The IPU consists of a randomly constructed LDPC code, an iterative decoder, a switch, and scaling and decision device. The quality of input images has been severely deteriorated for the purpose of mimicking visual information variability (VIV) experienced in human visual systems. The IPU is capable of (a) reliably recognizing digits from images of which quality is extremely inadequate; (b) achieving similar hyper-acuity performance comparing to human visual system; and (c) significantly improving the recognition rate with applying randomly constructed LDPC code, which is not specifically optimized for the tasks.
Show less
Date Issued: 2016
Identifier: CFE0006449, ucf:51413
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006449

Title: Creating a Consistent Oceanic Multi-decadal Intercalibrated TMI-GMI Constellation Data Record.
Creator: Chen, Ruiyao, Jones, W Linwood, Mikhael, Wasfy, Wei, Lei, Wilheit, Thomas, McKague, Darren, University of Central Florida
Abstract / Description: The Tropical Rainfall Measuring Mission (TRMM), launched in late November 1997 into a low earth orbit, produced the longest microwave radiometric data time series of 17-plus years from the TRMM Microwave Imager (TMI). The Global Precipitation Measuring (GPM) mission is the follow-on to TRMM, designed to provide data continuity and advance precipitation measurement capabilities. The GPM Microwave Imager (GMI) performs as a brightness temperature (Tb) calibration standard for the intersatellite...
Show moreThe Tropical Rainfall Measuring Mission (TRMM), launched in late November 1997 into a low earth orbit, produced the longest microwave radiometric data time series of 17-plus years from the TRMM Microwave Imager (TMI). The Global Precipitation Measuring (GPM) mission is the follow-on to TRMM, designed to provide data continuity and advance precipitation measurement capabilities. The GPM Microwave Imager (GMI) performs as a brightness temperature (Tb) calibration standard for the intersatellite radiometric calibration (XCAL) for the other constellation members; and before GPM was launched, TMI was the XCAL standard. This dissertation aims at creating a consistent oceanic multi-decadal Tb data record that ensures an undeviating long-term precipitation record covering TRMM-GPM eras. As TMI and GMI share only a 13-month common operational period, the U.S. Naval Research Laboratory's WindSat radiometer, launched in 2003 and continuing today provides the calibration bridge between the two. TMI/WindSat XCAL for their (>)9 years' period, and WindSat/GMI XCAL for one year are performed using a robust technique developed by the Central Florida Remote Sensing Lab, named CFRSL XCAL Algorithm, to estimate the Tb bias of one relative to the other. The 3-way XCAL of GMI/TMI/WindSat for their joint overlap period is performed using an extended CFRSL XCAL algorithm. Thus, a multi-decadal oceanic Tb dataset is created. Moreover, an important feature of this dataset is a quantitative estimate of the Tb uncertainty derived from a generic Uncertainty Quantification Model (UQM). In the UQM, various sources contributing to the Tb bias are identified systematically. Next, methods for quantifying uncertainties from these sources are developed and applied individually. Finally, the resulting independent uncertainties are combined into a single overall uncertainty to be associated with the Tb bias on a channel basis. This dissertation work is remarkably important because it provides the science community with a consistent oceanic multi-decadal Tb data record, and also allows the science community to better understand the uncertainty in precipitation products based upon the Tb uncertainties provided.
Show less
Date Issued: 2018
Identifier: CFE0006987, ucf:51650
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006987

Title: Method for Derivation and Synthesis of Electromagnetic Environmental Effects Requirement Limits for Achieving System Level Electromagnetic Compatibility.
Creator: Freeman, Larry, Wu, Thomas, Wahid, Parveen, Wei, Lei, Sundaram, Kalpathy, Chow, Louis, University of Central Florida
Abstract / Description: As humans endeavor to build large-scale complex systems, it will necessitate the integration of engineering practices and techniques to allocate many of the design aspects and responsibility across traditional boundaries. Many of today's large-scale complex systems, like commercial aircraft, satellite systems, and even automobiles use parts from all over the world. A recently completed airframe, largest commercial aircraft in the world, took nearly 30 years to build, required over 400...
Show moreAs humans endeavor to build large-scale complex systems, it will necessitate the integration of engineering practices and techniques to allocate many of the design aspects and responsibility across traditional boundaries. Many of today's large-scale complex systems, like commercial aircraft, satellite systems, and even automobiles use parts from all over the world. A recently completed airframe, largest commercial aircraft in the world, took nearly 30 years to build, required over 400 different suppliers from 20 different countries. These kinds of projects dictate a method for derivation and synthesis of electromagnetic environmental effects (E3) requirement limits for achieving system level electromagnetic compatibility (EMC).If a system level EMC design is an assemblage of compliant subsystems, then the subsystems should be an assemblage of compliant module and component designs. This requires tailoring the system level requirements through to module or component level designs. The method discussed is applicable to a variety of designs across varying levels of complexity and importantly implementable early in the design process. The method provides rationale for derivation of limits while maintaining traceability to system level requirements. Specific examples using the four common divisions of EMC requirements, conducted emissions, radiated emissions, conducted susceptibility, and radiated susceptibility are included. An overall system engineering approach and formal methodology is included. Detailed comparison examples using commercial and military EMC requirements are also included. Lastly, a discussion is included on comparison and margin analysis of input filtering for verifying compliance to requirements at the system level.
Show less
Date Issued: 2016
Identifier: CFE0006303, ucf:51603
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006303

Title: High Performance Techniques for Face Recognition.
Creator: Aldhahab, Ahmed, Mikhael, Wasfy, Atia, George, Jones, W Linwood, Wei, Lei, Elshennawy, Ahmad, University of Central Florida
Abstract / Description: The identification of individuals using face recognition techniques is a challenging task. This is due to the variations resulting from facial expressions, makeup, rotations, illuminations, gestures, etc. Also, facial images contain a great deal of redundant information, which negatively affects the performance of the recognition system. The dimensionality and the redundancy of the facial features have a direct effect on the face recognition accuracy. Not all the features in the feature...
Show moreThe identification of individuals using face recognition techniques is a challenging task. This is due to the variations resulting from facial expressions, makeup, rotations, illuminations, gestures, etc. Also, facial images contain a great deal of redundant information, which negatively affects the performance of the recognition system. The dimensionality and the redundancy of the facial features have a direct effect on the face recognition accuracy. Not all the features in the feature vector space are useful. For example, non-discriminating features in the feature vector space not only degrade the recognition accuracy but also increase the computational complexity.In the field of computer vision, pattern recognition, and image processing, face recognition has become a popular research topic. This is due to its wide spread applications in security and control, which allow the identified individual to access secure areas, personal information, etc. The performance of any recognition system depends on three factors: 1) the storage requirements, 2) the computational complexity, and 3) the recognition rates.Two different recognition system families are presented and developed in this dissertation. Each family consists of several face recognition systems. Each system contains three main steps, namely, preprocessing, feature extraction, and classification. Several preprocessing steps, such as cropping, facial detection, dividing the facial image into sub-images, etc. are applied to the facial images. This reduces the effect of the irrelevant information (background) and improves the system performance. In this dissertation, either a Neural Network (NN) based classifier or Euclidean distance is used for classification purposes. Five widely used databases, namely, ORL, YALE, FERET, FEI, and LFW, each containing different facial variations, such as light condition, rotations, facial expressions, facial details, etc., are used to evaluate the proposed systems. The experimental results of the proposed systems are analyzed using K-folds Cross Validation (CV).In the family-1, Several systems are proposed for face recognition. Each system employs different integrated tools in the feature extraction step. These tools, Two Dimensional Discrete Multiwavelet Transform (2D DMWT), 2D Radon Transform (2D RT), 2D or 3D DWT, and Fast Independent Component Analysis (FastICA), are applied to the processed facial images to reduce the dimensionality and to obtain discriminating features. Each proposed system produces a unique representation, and achieves less storage requirements and better performance than the existing methods.For further facial compression, there are three face recognition systems in the second family. Each system uses different integrated tools to obtain better facial representation. The integrated tools, Vector Quantization (VQ), Discrete cosine Transform (DCT), and 2D DWT, are applied to the facial images for further facial compression and better facial representation. In the systems using the tools VQ/2D DCT and VQ/ 2D DWT, each pose in the databases is represented by one centroid with 4*4*16 dimensions. In the third system, VQ/ Facial Part Detection (FPD), each person in the databases is represented by four centroids with 4*Centroids (4*4*16) dimensions. The systems in the family-2 are proposed to further reduce the dimensions of the data compared to the systems in the family-1 while attaining comparable results. For example, in family-1, the integrated tools, FastICA/ 2D DMWT, applied to different combinations of sub-images in the FERET database with K-fold=5 (9 different poses used in the training mode), reduce the dimensions of the database by 97.22% and achieve 99% accuracy. In contrast, the integrated tools, VQ/ FPD, in the family-2 reduce the dimensions of the data by 99.31% and achieve 97.98% accuracy. In this example, the integrated tools, VQ/ FPD, accomplished further data compression and less accuracy compared to those reported by FastICA/ 2D DMWT tools. Various experiments and simulations using MATLAB are applied. The experimental results of both families confirm the improvements in the storage requirements, as well as the recognition rates as compared to some recently reported methods.
Show less
Date Issued: 2017
Identifier: CFE0006709, ucf:51878
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006709

Title: RF Circuit Designs for Reliability and Process Variability Resilience.
Creator: Kritchanchai, Ekavut, Yuan, Jiann-Shiun, Sundaram, Kalpathy, Wei, Lei, Lin, Mingjie, Chow, Lee, University of Central Florida
Abstract / Description: Complementary metal oxide semiconductor (CMOS) radio frequency (RF) circuit design has been an ever-lasting research field. It has gained so much attention since RF circuits offer high mobility and wide-band efficiency, while CMOS technology provides the advantage of low cost and high integration capability. At the same time, CMOS device size continues to scale to the nanometer regime. Reliability issues with RF circuits have become more challenging than ever before. Reliability mechanisms,...
Show moreComplementary metal oxide semiconductor (CMOS) radio frequency (RF) circuit design has been an ever-lasting research field. It has gained so much attention since RF circuits offer high mobility and wide-band efficiency, while CMOS technology provides the advantage of low cost and high integration capability. At the same time, CMOS device size continues to scale to the nanometer regime. Reliability issues with RF circuits have become more challenging than ever before. Reliability mechanisms, such as gate oxide breakdown, hot carrier injection, negative bias temperature instability, have been amplified as the device size shrinks. In addition, process variability becomes a new design paradigm in modern RF circuits.In this Ph.D. work, a class F power amplifier (PA) was designed and analyzed using TSMC 180nm process technology. Its pre-layout and post-layout performances were compared. Post-layout parasitic effect decreases the output power and power-added efficiency. Physical insight of hot electron impact ionization and device self-heating was examined using the mixed-mode device and circuit simulation to mimic the circuit operating environment. Hot electron effect increases the threshold voltage and decreases the electron mobility of an n-channel transistor, which in turn decreases the output power and power-added efficiency of the power amplifier, as evidenced by the RF circuit simulation results. The device self-heating also reduces the output power and power-added efficiency of the PA. The process, voltage, and temperature (PVT) effects on a class AB power amplifier were studied. A PVT compensation technique using a current-source as an on-chip sensor was developed. The adaptive body bias design with the current sensing technique makes the output power and power-added efficiency much less sensitive to process variability, supply voltage variation, and temperature fluctuation, predicted by our derived analytical equations which are also verified by Agilent Advanced Design System (ADS) circuit simulation.Process variations and hot electron reliability on the mixer performance were also evaluated using different process corner models. The conversion gain and noise figure were modeled using analytical equations, supported by ADS circuit simulation results. A process invariant current source circuit was developed to eliminate process variation effect on circuit performance. Our conversion gain, noise figure, and output power show robust performance against PVT variations compared to those of a traditional design without using the current sensor, as evidenced by Monte Carlo statistical simulation.Finally, semiconductor process variations and hot electron reliability on the LC-voltage controlled oscillator (VCO) performance was evaluated using different process models. In our newly designed VCO, the phase noise and power consumptions are resilient against process variation effect due to the use of on-chip current sensing and compensation. Our Monte-Carlo simulation and analysis demonstrate that the standard deviation of phase noise in the new VCO design reduces about five times than that of the conventional design.
Show less
Date Issued: 2016
Identifier: CFE0006131, ucf:51182
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0006131

Title: Post Conversion Correction of Non-Linear Mismatches for Time Interleaved Analog-to-Digital Converters.
Creator: Parkey, Charna, Mikhael, Wasfy, Qu, Zhihua, Georgiopoulos, Michael, Myers, Brent, Wei, Lei, Chester, David, University of Central Florida
Abstract / Description: Time Interleaved Analog-to-Digital Converters (TI-ADCs) utilize an architecture which enables conversion rates well beyond the capabilities of a single converter while preserving most or all of the other performance characteristics of the converters on which said architecture is based. Most of the approaches discussed here are independent of architecture; some solutions take advantage of specific architectures. Chapter 1 provides the problem formulation and reviews the errors found in ADCs as...
Show moreTime Interleaved Analog-to-Digital Converters (TI-ADCs) utilize an architecture which enables conversion rates well beyond the capabilities of a single converter while preserving most or all of the other performance characteristics of the converters on which said architecture is based. Most of the approaches discussed here are independent of architecture; some solutions take advantage of specific architectures. Chapter 1 provides the problem formulation and reviews the errors found in ADCs as well as a brief literature review of available TI-ADC error correction solutions. Chapter 2 presents the methods and materials used in implementation as well as extend the state of the art for post conversion correction. Chapter 3 presents the simulation results of this work and Chapter 4 concludes the work. The contribution of this research is three fold: A new behavioral model was developed in SimulinkTM and MATLABTM to model and test linear and nonlinear mismatch errors emulating the performance data of actual converters. The details of this model are presented as well as the results of cumulant statistical calculations of the mismatch errors which is followed by the detailed explanation and performance evaluation of the extension developed in this research effort. Leading post conversion correction methods are presented and an extension with derivations is presented. It is shown that the data converter subsystem architecture developed is capable of realizing better performance of those currently reported in the literature while having a more efficient implementation.
Show less
Date Issued: 2015
Identifier: CFE0005683, ucf:50171
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005683

Title: Multi-Physics Model of Key Components In High Efficiency Vehicle Drive.
Creator: Lin, Shao Hua, Wu, Xinzhang, Sundaram, Kalpathy, Wahid, Parveen, Wei, Lei, Chow, Louis, University of Central Florida
Abstract / Description: Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs) are crucial technologies for the automotive industry to meet society's demands for cleaner, more energy efficient transportation. Meeting the need to provide power which sustains HEVs and EVs is an immediate area of concern that research and development within the automotive community must address. Electric batteries and electrical motors are the key components in HEV and EV power generation and transmission, and their performance...
Show moreHybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs) are crucial technologies for the automotive industry to meet society's demands for cleaner, more energy efficient transportation. Meeting the need to provide power which sustains HEVs and EVs is an immediate area of concern that research and development within the automotive community must address. Electric batteries and electrical motors are the key components in HEV and EV power generation and transmission, and their performance plays very important role in the overall performance of the modern high efficiency vehicles. Therefore, in this dissertation, we are motivated to study the electric batteries, interior permanent motor (IPM), in the context of modern hybrid electric/electric drive systems, from both multi-physics and system level perspectives. Electrical circuit theory, electromagnetic Finite Element Analysis (FEA), and Computational Fluid Dynamic (CFD) finite volume method will be used primarily in this work. The work has total of five parts, and they are introduced in the following.Firstly, Battery thermal management design is critical in HEV and EV development. Accurate temperature distribution of the battery cells during vehicle operation is required for achieving optimized design. We propose a novel electrical-thermal battery modeling technique that couples a temperature dependent battery circuit model and a physics-based CFD model to meet this need. The electrical circuit model serves as a heat generation mechanism for the CFD model, and the CFD model provides the temperature distribution of the battery cells, which can also impact the heat generation of the electrical battery model. In this part of work, simulation data has been derived from the model respective to electrical performance of the battery as well as the temperature distribution simultaneously in consideration of the physical dimensions, material properties, and cooling conditions. The proposed model is validated against a battery model that couples the same electrical model with a known equivalent thermal model.Secondly, we propose an accurate system level Foster network thermal model. The parameters of the model are extracted from step responses of the CFD battery thermal model. The Foster network model and the CFD model give the same results. The Foster network can couple with battery circuit model to form an electric-thermal battery model for system simulation.Thirdly, IPM electric machines are important in high performance drive systems. During normal operations, irreversible demagnetization can occur due to temperature rise and various loading conditions. We investigate the performance of an IPM using 3d time stepping electromagnetic FEA considering magnet's temperature dependency. Torque, flux linkage, induced voltage, inductance and saliency of the IPM will be studied in details. Finally, we use CFD to predict the non-uniform temperature distribution of the IPM machine and the impact of this distribution on motor performance. Fourthly, we will switch gear to investigate the IPM motor on the system level. A reduced order IPM model is proposed to consider the effect of demagnetization of permanent magnet due to temperature effect. The proposed model is validated by comparing its results to the FEA results.Finally, a HEV is a vehicle that has both conventional mechanical (i.e. internal combustion engine) and electrical propulsion systems. The electrical powertrain is used to work with the conventional powertrain to achieve higher fuel economy and lower emissions. Computer based modeling and simulation techniques are therefore essential to help reduce the design cost and optimize system performance. Due to the complexity of hybrid vehicles, multi-domain modeling ability is preferred for both component modeling and system simulation. We present a HEV library developed using VHDL-AMS.
Show less
Date Issued: 2013
Identifier: CFE0005024, ucf:50016
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005024

Title: Time and Space Efficient Techniques for Facial Recognition.
Creator: Alrasheed, Waleed, Mikhael, Wasfy, DeMara, Ronald, Haralambous, Michael, Wei, Lei, Myers, Brent, University of Central Florida
Abstract / Description: In recent years, there has been an increasing interest in face recognition. As a result, many new facial recognition techniques have been introduced. Recent developments in the field of face recognition have led to an increase in the number of available face recognition commercial products. However, Face recognition techniques are currently constrained by three main factors: recognition accuracy, computational complexity, and storage requirements. The problem is that most of the current face...
Show moreIn recent years, there has been an increasing interest in face recognition. As a result, many new facial recognition techniques have been introduced. Recent developments in the field of face recognition have led to an increase in the number of available face recognition commercial products. However, Face recognition techniques are currently constrained by three main factors: recognition accuracy, computational complexity, and storage requirements. The problem is that most of the current face recognition techniques succeed in improving one or two of these factors at the expense of the others.In this dissertation, four novel face recognition techniques that improve the storage and computational requirements of face recognition systems are presented and analyzed. Three of the four novel face recognition techniques to be introduced, namely, Quantized/truncated Transform Domain (QTD), Frequency Domain Thresholding and Quantization (FD-TQ), and Normalized Transform Domain (NTD). All the three techniques utilize the Two-dimensional Discrete Cosine Transform (DCT-II), which reduces the dimensionality of facial feature images, thereby reducing the computational complexity. The fourth novel face recognition technique is introduced, namely, the Normalized Histogram Intensity (NHI). It is based on utilizing the pixel intensity histogram of poses' subimages, which reduces the computational complexity and the needed storage requirements. Various simulation experiments using MATLAB were conducted to test the proposed methods. For the purpose of benchmarking the performance of the proposed methods, the simulation experiments were performed using current state-of-the-art face recognition techniques, namely, Two Dimensional Principal Component Analysis (2DPCA), Two-Directional Two-Dimensional Principal Component Analysis ((2D)^2PCA), and Transform Domain Two Dimensional Principal Component Analysis (TD2DPCA). The experiments were applied to the ORL, Yale, and FERET databases.The experimental results for the proposed techniques confirm that the use of any of the four novel techniques examined in this study results in a significant reduction in computational complexity and storage requirements compared to the state-of-the-art techniques without sacrificing the recognition accuracy.
Show less
Date Issued: 2013
Identifier: CFE0005297, ucf:50566
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005297

Title: CONAE MicroWave Radiometer (MWR) Counts to Brightness Temperature Algorithm.
Creator: Ghazi, Zoubair, Jones, W Linwood, Wei, Lei, Mikhael, Wasfy, Wu, Thomas, Junek, William, Piepmeier, Jeffrey, University of Central Florida
Abstract / Description: This dissertation concerns the development of the MicroWave Radiometer (MWR) brightness temperature (Tb) algorithm and the associated algorithm validation using on-orbit MWR Tb measurements. This research is sponsored by the NASA Earth Sciences Aquarius Mission, a joint international science mission, between NASA and the Argentine Space Agency (Comision Nacional de Actividades Espaciales, CONAE). The MWR is a CONAE developed passive microwave instrument operating at 23.8 GHz (K-band) H-pol...
Show moreThis dissertation concerns the development of the MicroWave Radiometer (MWR) brightness temperature (Tb) algorithm and the associated algorithm validation using on-orbit MWR Tb measurements. This research is sponsored by the NASA Earth Sciences Aquarius Mission, a joint international science mission, between NASA and the Argentine Space Agency (Comision Nacional de Actividades Espaciales, CONAE). The MWR is a CONAE developed passive microwave instrument operating at 23.8 GHz (K-band) H-pol and 36.5 GHz (Ka-band) H- (&) V-pol designed to complement the Aquarius L-band radiometer/scatterometer, which is the prime sensor for measuring sea surface salinity (SSS). MWR measures the Earth's brightness temperature and retrieves simultaneous, spatially collocated, environmental measurements (surface wind speed, rain rate, water vapor, and sea ice concentration) to assist in the measurement of SSS.This dissertation research addressed several areas including development of: 1) a signal processing procedure for determining and correcting radiometer system non-linearity; 2) an empirical method to retrieve switch matrix loss coefficients during thermal-vacuum (T/V) radiometric calibration test; and 3) an antenna pattern correction (APC) algorithm using Inter-satellite radiometric cross-calibration of MWR with the WindSat satellite radiometer. The validation of the MWR counts-to-Tb algorithm was performed using two years of on-orbit data, which included special deep space calibration measurements and routine clear sky ocean/land measurements.
Show less
Date Issued: 2014
Identifier: CFE0005496, ucf:50366
Format: Document (PDF)
PURL: http://purl.flvc.org/ucf/fd/CFE0005496

UWB (4)	+ -
Cognitive Radio (2)	+ -
ESD (2)	+ -
OFDM (2)	+ -
TRMM (2)	+ -

Temperature (2)	+ -
connectivity (2)	+ -
(2D)^2PCA (1)	+ -
2DPCA (1)	+ -
Active Mixer (1)	+ -
Advanced Coding (1)	+ -
Amplifier (1)	+ -
Aquarius (1)	+ -
Argumentation (1)	+ -
Battery (1)	+ -
CFD (1)	+ -
CMOS (1)	+ -
CONOE Microwave Radiometer (1)	+ -
Channel Model (1)	+ -
Charge Injection (1)	+ -
Coherent Fiber Communication (1)	+ -
Compressive Sensing (1)	+ -
Coupling Unit (1)	+ -
DCT (1)	+ -
Density Evolution (1)	+ -
Digital Backward Propagation (1)	+ -
Digital Modulation (1)	+ -
Diode (1)	+ -
Discrete Cosine Transform (1)	+ -
Discrete Multiwavelet Transform (1)	+ -

University of Central Florida (32)	+ -
Wei, Lei (29)	+ -
Mikhael, Wasfy (8)	+ -
Sundaram, Kalpathy (7)	+ -
Atia, George (4)	+ -

Jones, W Linwood (4)	+ -
Rahnavard, Nazanin (4)	+ -
Vosoughi, Azadeh (4)	+ -
Lin, Mingjie (3)	+ -
Yuan, Jiann-Shiun (3)	+ -
Chatterjee, Mainak (2)	+ -
Chow, Louis (2)	+ -
Fan, Deliang (2)	+ -
Jin, Yier (2)	+ -
Myers, Brent (2)	+ -
Qu, Zhihua (2)	+ -
Salcedo, Javier (2)	+ -
Sukthankar, Gita (2)	+ -
Turgut, Damla (2)	+ -
Wahid, Parveen (2)	+ -
Wilheit, Thomas (2)	+ -
Wu, Thomas (2)	+ -
Wu, Xinzhang (2)	+ -
Al-tameemi, Osama (1)	+ -
Alabri, Said (1)	+ -
Aldhahab, Ahmed (1)	+ -
Alquaied, Faisal (1)	+ -
Alrasheed, Waleed (1)	+ -
Bassiouni, Mostafa (1)	+ -
Berksoy, Burak (1)	+ -

Search In

Pages

Pages

Sort Results By:

Narrow results by:

Topical Subject

Collection

Type of Resource

Language

Creator

Format

Owner