No description available.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1992. / Vita. Abstract. Includes bibliographical references (leaves 60-63). Also available via the Internet.

Thesis (M. Phil.)--University of Hong Kong, 1993. / Photocopy typescript.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1983. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 106-111).

No description available.

In many applications, it is necessary to simulate wave scattering from surfaces that have small radii of curvature relative to the incident wavelength. Surface features smaller than an electromagnetic wavelength are known to create diffracted fields over a wide range of scattering angles. In this thesis, the significance of such effects at low grazing angles with the presence of an extended planar surface is considered. The magnetic field integral equation (MFIE) describing the currents on such surfaces is used to solve for the bistatic scattered fields. The integral equations are discretized using the moment method and solved using the Method of Ordered Multiple Interactions (MOMI) iterative procedure. This thesis will concentrate on normal incidence and low grazing angle (LGA) incidence, specifically an incident angle of 80 degrees. The surface used in the analysis is a one-dimensional, perfectly-conducting wedge-on-a-plane with a varying radius of curvature at the wedge tip and Gaussian tails that smoothly extend the wedge to the plane surface. This surface displays continuous first and second derivatives over the entire surface. The radius of curvature at the wedge tip is varied between 0.0125 wavelengths and 8 wavelengths. The form of the bistatic scattered fields will be investigated for three different wedge height to wedge width geometries. The surface scattering mechanisms and their respective location and form in the scattered field will be discussed. The dependence of the scattered field pattern on the radius of curvature at the wedge tip and the beam width of the incident field will be considered. The difficulties associated with using a numerical technique on extended surfaces where a significant source of diffracted energy is present will also be examined. This includes the issue of sampling a surface that contains areas of small radii of curvature and the issue of surface truncation when significant currents due to tip diffraction are produced well outside the illuminated area. Both TE (VV) and TM (HH) polarization will be considered. This thesis also analyzes the scattered fields for a perfect electric conducting (PEC) ridge and well in the presence of an extended planar surface for an incident angle of 70 degrees. The dual-surface magnetic field integral equation (DMFIE) formulation for a one-dimensional extended surface will be used to solve for the unknown currents on the surface of the scatterer. The DMFIE formulation leads to a second kind integral equation that can be solved via the MOMI series with the proper choice of the parameters appearing in the DMFIE formulation. The bistatic scattered fields for several ridge and well geometries are examined for both TE and TM polarization. / Master of Science

Moore’s law states that the number of transistors in an Integrated Circuit (IC) doubles every two years. Ever-increasing performance in mask writing machinery is therefore required being the first step in the manufacturing process. Many factors affect the quality of the end product, with the motion control system playing an important role. This thesis analyzes the performance of the motion controller for the positioning system in a mask writer application. The target motion in the X-axis in the mask writer is by design highly repetitive and predictable. As of today a feedforward-feedback controller is used, tuned for low deviation during writing. In this thesis it is found that the motion control can be improved by exploiting the repetitive nature of the motion task. Two iterative methods are explored, Iterative Feedback Tuning (IFT) and Iterative Learning Control (ILC). IFT is implemented as a parameter optimizing method for the existing Proportional-Integral-Derivative (PID) controller. Given suboptimal initial parameters the algorithm converges to a global minimum using a cost function to minimize total deviation and constraints on the maximum deviation. With the optimized parameter settings an improvement of a 31 % decrease in total deviation is seen compared to the default setting. ILC is implemented as a replacement to the current controller in an exposure motion. With the use of saved data from previous iterations the control signal is updated and refined to better suit the target motion. ILC is a promising method within high precision motion control by virtue of not needing a model of the system and its ability to suppress reoccurring disturbances. The algorithm achieves an improvement of a 94% decrease in total deviation during writing compared to the current controller. However, with this implementation long term stability is not guaranteed. A stable implementation of the algorithm tested on a test rig achieves an improvement of a 79.8% decrease in deviation during writing compared to the current feedforward-feedback controller. Additionally, correlations between parameter values of the current feedback controller and servo characteristics are analyzed to aid in the manual tuning process. Tuning the PID controller for fast rise time decreases the total deviation during writing. The derivative gain in the controller should be high to decrease the overshoot caused by the aggressive controller. This will induce some oscillations into the system, however not at the cost of performance as a result of the smooth motion during writing.

No description available.

No description available.

As the current rate of improvement in processor performance far exceeds the rate of memory performance, memory latency is the dominant overhead in many performance critical applications. In many cases, automatic compiler-based approaches to improving memory performance are limited and programmers frequently resort to manual optimisation techniques. However, this process is tedious and time-consuming. Furthermore, a diverse range of a rapidly evolving hardware makes the optimisation process even more complex. It is often hard to predict the potential benefits from different optimisations and there are no simple criteria to stop optimisations i.e. when optimal memory performance has been achieved or sufficiently approached. This thesis presents a platform independent optimisation approach for numerical applications based on iterative feedback-directed program restructuring using a new reasonably fast and accurate performance prediction technique for guiding optimisations. New strategies for searching the optimisation space, by means of profiling to find the best possible program variant, have been developed. These strategies have been evaluated using a range of kernels and programs on different platforms and operating systems. A significant performance improvement has been achieved using new approaches when compared to the state-of-the-art native static and platform-specific feedback directed compilers.