Multiple input multiple output (MIMO) systems using multiple transmit and receive antennas are widely considered as the vital breakthrough that will allow future wireless systems to achieve higher date rates and link reliability with limited bandwidth and power resources. In this dissertation, we address four interesting topics in the wireless MIMO systems, in both point-to-point and multiuser environments. First, in a point-to-point MIMO spatial diversity system, usually the probability distribution function (PDF) of the received SNR is rather involved, which leads to the difficulty in analyzing the average symbol error rate (SER). We provide a succinct result at the high SNR region. Second, in point-to-point wireless MIMO communications, in order to protect the transmitted data against random channel impairment, we consider the problem of link adaptation, including rate adaptation and power control to improve the system performance and guarantee certain quality of service. Third, in a multiuser MIMO wireless network, there is another form of diversity called multiuser diversity which can be exploited to increase the system throughput. By analyzing the scheduling gain (defined as the rate difference between the opportunistic scheduling and round-robin scheduling scheme), we provide a complete analysis on the interaction between the spatial diversity and multiuser diversity. Fourth, in a multiuser MIMO wireless network, we propose a crosslayer-based scheduling scheme that exploits Tomlinson-Harashima Precoding (THP) at the physical (PHY) layer to reduce the multiuser scheduling burden at the medium access control (MAC) layer. Compared with some existing scheduling schemes, the proposed scheme greatly reduces the scheduling complexity while simultaneously improves overall system performance.

Magnetic Resonance Imaging (MRI) is one of the most widely used clinical diagnostic procedures. Evaluation of safety due to Radio Frequency (RF) energy deposition and tissue heating in patients during MRI, especially in the presence of implantable prosthetic devices is significant for MR safety. The work presented in this thesis aims to characterize the interactions between the pulsed RF fields during MRI and biological tissues of a patient with a Retinal Prosthesis (RP) implant, in terms of Specific Absorption Rate (SAR) and temperature elevation. A logarithmically expanding grid Finite-Difference Time-Domain (FDTD) is used for computational modeling of the MR environment at 64, 128 and 256 MHz. Unlike traditional methods, expanding grid FDTD facilitates in accurate modeling of the region of the implant where a finer grid with cell sizes of the order of micrometers is used. Also, this technique greatly helps to reduce the constraints on computational memory and time. It was found that, while the RF magnetic field, B1, homogeneity decreases with frequency; power deposition in the tissues increases slightly. However, thermal elevation resulting from the SAR distribution as well as the induced currents in the RP implant, evaluated using the bio-heat equation, is observed to be minimal at these frequencies. These results provide useful information for RF safety guidelines during MRI at high fields.

This dissertation presents an assessment of the worst case stresses produced in an induction motor when the motor is allowed to ride through a power supply voltage disturbance. Results from laboratory experiments and computer simulations are shown. The experimental results are obtained from tests conducted on three squirrel cage induction motors, sized 10 hp, 50 hp, and 75 hp. Each motor is tested with three different load inertias, various motor loadings, and numerous interruption durations. The computer simulation results are obtained using a non-linear motor-load model, whose parameters are derived from a non-linear least squares parameter estimation technique. Experimental data acquired in the lab is used for the parameter estimation data and for the validation data. Deficiencies in the standard motor-load model are presented and addressed. Good agreement between the experimental data and the non-linear motor-load model data is achieved. Results show significant current and torque transients, but caused no significant damage to the motors or loads used for testing.

As the complexity of SoC design grows, the traditional register transfer level (RTL) centric design flow cannot meet the time to market. In that case, a higher modeling level of abstraction is need for designer to explore the design space at system level. Transaction-level model (TLM) is such an approach since it could run much faster than RTL model and also have enough accuracy. There are different modeling styles of TLM for different applications. In this thesis, we develop a hybrid-TLM of Network-on-chip (NoC) based on OSCI TLM-2.0 standard. We use a simplified version of the AMBA AXI protocol for the bus. This model contains a cycle-accurate AXI router and other periphery modules with approximately-timed coding style, which achieve fast simulation speed and accurate result. This model keeps good interoperability since it entirely based on TLM-2.0 standard. And the designer could build complex NoCs by making use of this model.

This thesis develops an algorithm for shape representation and matching. The algorithm is an object centered, boundary based method for shape recognition. Global features of the shape are utilized to define a frame of reference relative to which local shape features are characterized. The curvature of the boundary at a point is the local feature used. Curvature is computed by the Digital Straight Segments algorithm. Matching is done using the process of evidence accumulation similar in approach to the Generalized Hough Transform. The algorithm is tested for invariance to similarity transforms. Its robustness to noise and blurring is also tested. A multi-layer, feed-forward neural network architecture that implements the algorithm is proposed.

This dissertation develops novel methods to reconstruct a three-dimensional surface together with a characterization of the surface composition given one or more images obtained from the same viewing direction. First, a vector space method to reconstruct a surface given a gradient field is developed using the linear relationship between a surface and its gradient field in discrete surface domains. The developed gradient field representation is generalized to alleviate the common assumption of uniform integrability in gradient fields to partial integrability, allowing adequate reconstruction of surfaces with non-integrable gradient fields. In addition, the developed technique is further explored for gradient field noise reduction, by embedding multiscale properties providing sparse gradient field representations. Next, the ambiguity in possible surface gradients obtained by a two-image photometric stereo analysis is resolved using a cyclic projections algorithm based on the set of possible gradient fields and the previously developed gradient field representation. An algorithm that provides accurate surface reconstructions and surface type characterizations given two images of an unknown composite surface is established. We then apply this algorithm to Scanning Electron Microscopy (SEM) images to extract specimen surface topography and material type information from a pair of Secondary Electron (SE) and Back-scattered Electron (BSE) images. We then use a similar cyclic projections algorithm to reconstruct a surface from a single image. The simulation results indicate that the developed algorithm solves this classical shape-from-shading problem in a robust and accurate manner for varying illumination conditions. Finally, we establish a unified surface reconstruction framework using previously developed techniques on a photometric stereo image triplet containing shadows. We categorize the surface pixels as those illuminated in all three images, only two images and only one image. We then establish through simulation results that the developed method uses the surface gradient information obtained from the brightness images efficiently and effectively, and provides an accurate surface reconstruction.

As various wireless networks evolves into the next generation to provide better services, a key technology, mobile ad hoc networks (MANETs), has emerged recently. The dynamic topology, multi-hop transmission, and the nature of wireless channels create many challenging research topics in the area of MANETs. Recently, there has been work on determining the capacity of MANETs. The effects of some factors, such as node mobility, number of nodes, and transmission range, on the capacity of MANETs have been considered. In this work, we define and investigate the capacity of MANETs, considering the effects of medium access control (MAC). Since all the nodes in MANETs use a single or multiple channels to communicate, MAC plays an important role in coordinating channel access among nodes so that information gets through from one node to another. The MAC affects the capacity of MANETs in two aspects: collisions and spatial reuse. Three basic mechanisms are adopted to eliminate the incidence of collisions and maximize spatial reuse, i.e., carrier sense, handshake, and back-off. We define and use persistent probability, sensing range and back-off time to represent the effect of these mechanisms. The characteristics of MAC are thoroughly examined and an analytical solution for capacity evaluation is proposed. Numerical results are presented to demonstrate the effects of MAC, including carrier sense, handshake and back-off mechanism on the capacity of MANETs in terms of persistent probability, sensing range, and back-off time.

Recent experimental and physical modeling studies demonstrate that, as opposed to systems with smaller bandwidth, the Ultra-Wideband (UWB) channel exhibits frequency-dependent distortion of individual multipath components. This per-path distortion is particularly significant in outdoor UWB applications, where line-of-sight (LOS) or non-distorted reflected signals might not be available at the receiver (for example, in a canyon-like street). In these cases, the dominant propagation mechanisms involve shadowing (diffraction) and reflection by small objects (e.g. signs or lamp-posts). In this dissertation, a physical model is developed to investigate the position-dependent distortion of the UWB pulse. The results indicate that both the shadowed pulse and the reflected pulse (by small objects with dimensions bounded by the wavelengths present in the signal) are distorted. Design of optimal and suboptimal templates for the correlation receiver are investigated. The UWB pulses that accommodate robust template choice given by the transmit pulse shape for all propagation conditions and satisfy the FCC spectral mask for outdoor channels are identified. Finally, we analyze the frequency-dependent propagation gain of the UWB channels in various outdoor conditions. This knowledge quantifies the potential benefits of adapting the transmitted signal to the dominant propagation mechanism.

Techniques used to model a field-effect transistor's equivalent circuit parameters are investigated and applied to an on-wafer AlGaN/GaN HFET using high-frequency S-parameters. Analysis of a THRU line allowed substrate permittivity characterization, improving parasitic capacitance estimation. Drain-source output admittance dispersion was observed in the measured devices. This dispersion phenomena was attributed to parallel conduction and was primarily present for low drain-source bias. Dispersion complicated parameter calculation and required modification of commonly used model extraction techniques. Effective mobility was also estimated by only using information contained in the S-parameter measurements. Small-signal parameter temperature dependence was also investigated to determine each parameter's associated temperature coefficient.

Performances of closed-loop control systems operated over a data network are typically degraded by network-induced delays. Furthermore, the closed-loop control systems can become unstable. The purpose of this research has been to develop a control methodology to handle network-induced delay effects using optimal gain scheduling on existing controllers. The proposed gain scheduling technique adapts controller gains externally by modifying a controller output to enable the controller for uses over a data network. Since existing controllers can still be utilized, the proposed methodology can reduce control system reinstallation and replacement costs. First, the effectiveness of the proposed gain scheduling technique on networked DC motor speed control using a PI (Proportional-Integral) controller is investigated. Also, the concept of network traffic condition measurement to select optimal controller gains is presented. Then, a middleware framework to measure network traffic conditions on an IP network based on delays and delay variations and to modify controller gains is described. Suggestion of using neural network in the gain scheduling scheme is also given. Finally, the gain scheduling technique with the middleware framework is then extended to mobile robot path-tracking control.