A passive wireless surface acoustic wave sensor of a delay-line type is composed of an antenna, a transducer that converts the EM signal into a surface acoustic wave, and a set of acoustic reflectors that reflect the incoming signal back out through the antenna. A cavity forms between the transducer and the reflectors, trapping energy and causing multiple unwanted echoes. The work in this dissertation aims to reduce the unwanted echoes so that only the main transit signal is left--the signal of interest with sensor information. The contributions of this dissertation include reflective delay-line device response in the form of an infinite impulse response (IIR) filter. This may be used in the future to subtract out unwanted echoes via post-processing. However, this dissertation will use a physical approach to echo suppression by using a unidirectional transducer. Thus a unidirectional transducer is used and also optimized for 3rd harmonic operation. Both the directionality and the coupling of the 3rd harmonic optimized SPUDT are improved over a standard electrode width controlled (EWC) SPUDT. New type of reflectors for the reflective delay-line device are also presented. These use BPSK type coding, similar to that of the Walsh-Hadamard codes. Two types are presented, variable reflectivity and variable chip-lengths. The COM model is used to simulate devices and compare the predicted echo suppression level to that of fabricated devices. Finally, a device is mounted on a tunable antenna and the echo is suppressed on a wireless operating device.

This thesis proposes a new class of bivariate autoregressive conditional median duration models for matched high-frequency data and develops some inferential methods for an existing univariate model as well as the bivariate models introduced here to facilitate model fitting and forecasting. During the last two decades, the autoregressive conditional mean duration (ACD) model has been playing a dominant role in analyzing irregularly spaced high-frequency financial data. Univariate ACD models have been extensively discussed in the literature. However, some major challenges remain. The existing ACD models do not provide a good distributional fit to financial durations, which are right-skewed and often exhibit unimodal hazard rates. Birnbaum-Saunders (BS) distribution is capable of modeling a wide variety of positively skewed data. Median is not only a robust measure of central tendency, but also a natural scale parameter of the BS distribution. A class of conditional median duration models, the BS-ACD and the scale-mixture BS ACD models based on the BS, BS power-exponential and Student-t BS (BSt) distributions, have been suggested in the literature to improve the quality of the model fit. The BSt-ACD model is more flexible than the BS-ACD model in terms of kurtosis and skewness. In Chapter 2, we develop the maximum likelihood estimation method for the BSt-ACD model. The estimation is performed by utilizing a hybrid of optimization algorithms. The performance of the estimates is then examined through an extensive Monte Carlo simulation study. We also carry out model discrimination using both likelihood-based method and information-based criterion. Applications to real trade durations and comparison with existing alternatives are then made. The bivariate version of the ACD model has not received attention due to non-synchronicity. Although some bivariate generalizations of the ACD model have been introduced, they do not possess enough flexibility in modeling durations since they are conditional mean-based and do not account for non-monotonic hazard rates. Recently, the bivariate BS (BVBS) distribution has been developed with many desirable properties and characteristics. It allows for unimodal shapes of marginal hazard functions. In Chapter 3, upon using this bivariate BS distribution, we propose the BVBS-ACD model as a natural bivariate extension of the BS-ACD model. It enables us to jointly analyze matched duration series, and also capture the dependence between the two series. The maximum likelihood estimation of the model parameters and associated inferential methods have been developed. A Monte Carlo simulation study is then carried out to examine the performance of the proposed inferential methods. The goodness-of-fit and predictive performance of the model are also discussed. A real bivariate duration data analysis is provided to illustrate the developed methodology. The bivariate Student-t BS (BVBSt) distribution has been introduced in the literature as a robust extension of the BVBS distribution. It provides greater flexibility in terms of the kurtosis and skewness through the inclusion of an additional shape parameter. In Chapter 4, we propose the BVBSt-ACD model as a natural extension of the BSt-ACD model to the bivariate case. We then discuss the maximum likelihood estimation of the model parameters. A simulation study is carried out to investigate the performance of these estimators. Model discrimination is then done by using information-based criterion. Methods for evaluating the goodness-of-fit and predictive ability of the model are also discussed. A simulated data example is used to illustrate the proposed model as compared to the BVBS-ACD model. Finally, in Chapter 5, some concluding comments are made and also some problems for future research are mentioned. / Thesis / Master of Science (MSc)

Over the last two decades, great progress has been made in the understanding of multiferroic materials, ones where multiple long-range orders simultaneously exist. However, much of the research has focused on bulk systems. If these materials are to be incorporated into devices, they would not be in bulk form, but would be miniaturized, such as in nanoparticle form. Accordingly, a better understanding of multiferroic nanoparticles is necessary. This manuscript examines the multiferroic phase diagram of multiferroic nanoparticles related to system size and surface-induced magnetic anisotropy. There is a particular focus on bismuth ferrite, the room-temperature antiferromagnetic-ferroelectric multiferroic. Theoretical results will be presented which show that at certain sizes, a bistability develops in the cycloidal wavevector. This implies bistability in the ferroelectric and magnetic moments of the nanoparticles. This novel magnetoelectric bistability may be of use in the creation of an electrically-written, magnetically-read memory element. / Graduate