No / An efficient way to test for potential unsymmetrical nonlinear responses in biological tissue samples exposed to a microwave signal is to observe the second harmonic in a cavity resonant at the two frequencies, with collocated antinodes. Such a response would be of interest as being a mechanism that could enable demodulation of information-carrying waveforms. In this work, an electric circuit model is proposed to facilitate calibration of any putative nonlinear RF energy conversion inside a high quality-factor resonant cavity with a known nonlinear loading device. The first and second harmonic responses of the cavity due to loading with the nonlinear and lossy material are also demonstrated. The results from the proposed mathematical model give a good indication of the input power required to detect any very weak second harmonic signal in relation to the sensitivity of the measurement equipment. Hence, this proposed mathematical model will assist in determining the level of the second harmonic signal in the detector as a function of the specific input power applied. / EPSRC

"Previous implementations of digital background calibration for cyclic ADCs have required linear amplifier behavior in the gain stage for accurate correction. Correction is digital decoding of ADC outputs to determine the original ADC input. Permitting nonlinearity in the gain stage of the ADC allows for less demanding amplifier design requirements, reducing power and size. However this requires a method of determining the value of this variable gain during digital correction. Look up tables (LUTs,) are an effective and efficient method of compensating for analog circuit imperfections. The LUT correction and calibration method discussed in this work has been simulated using Cadence integrated circuit simulation ADC specifications and MATLAB."

Digital predistortion is one of the most cost effective ways among all linearization techniques. However, most of the existing designs treat the power amplifier as a memoryless device. For wideband or high power applications, the power amplifier exhibits memory effects, for which memoryless predistorters can achieve only limited linearization performance. In this dissertation, we propose novel predistorters and their parameter extraction algorithms. We investigate a Hammerstein predistorter, a memory polynomial predistorter, and a new combined model based predistorter. The Hammerstein predistorter is designed specifically for power amplifiers that can be modeled as a Wiener system. The memory polynomial predistorter can correct both the nonlinear distortions and the linear frequency response that may exist in the power amplifier. Real-time implementation aspects of the memory polynomial predistorter are also investigated. The new combined model includes the memory polynomial model and the Murray Hill model, thus extending the predistorter's ability to compensate for strong memory effects in the power amplifier. The predistorter models considered in this dissertation include both even- and odd-order nonlinear terms. By including these even-order nonlinear terms, we have a richer basis set, which offers appreciable improvement. In reality, however, the performance of a predistortion system can also be affected by the analog imperfections in the transmitter, which are introduced by the analog components; mostly analog filters and quadrature modulators. There are two common configurations for the upconversion chain in the transmitter: two-stage upconversion and direct upconversion. For a two-stage upconversion transmitter, we design a band-limited equalizer to compensate for the frequency response of the surface acoustic wave (SAW) filter which is usually employed in the IF stage. For a direct upconversion transmitter, we develop a model to describe the frequency-dependent gain/phase imbalance and dc offset. We then develop two methods to construct compensators for the imbalance and dc offset. These compensation techniques help to correct for the analog imperfections, which in turn improve the overall predistortion performance.

No description available.

Abstract Axially moving material problems are concerned with the dynamic response, vibration and stability of slender members which are in a state of translation. In Finland these are particularly important in the functioning of paper machines, in which out of plane vibration in the paper web, known as flutter, which from the point of view of mechanics is a phenomenon typical of an axially moving material, limits operation speeds and therefore the productivity of the machines. This subject links together a number of physical phenomena associated with aerodynamics, web movement, material behaviour and the geometry of the system. The aim of this research is to present a theoretical and numerical formulation of the nonlinear dynamic analysis of an axially moving web. The theoretical model is based on a mixed description of the continuum problem in the context of the dynamics of initially stressed solids. Membrane elasticity is included via a finite strain model, and the membrane transport speed through a kinematical study. Hamilton's principle provides nonlinear equations which describe the three-dimensional motion of the membrane. The incremental equations of Hamilton's principle are discretized by the finite element method. The formulation includes geometrically nonlinear effects: large displacements, variations in membrane tension and variations in transport velocity due to deformation. This novel numerical model was implemented by adding an axially moving membrane element to a FEM program which contains acoustic fluid elements and contact algorithms. This allowed analysis of problems including interaction with the surrounding air field and contact between supporting structures. The model was tested by comparing previous experiments and present nonlinear description of the dynamic behaviour of an axially moving web. The effects of contact between finite rolls and the membrane and interaction between the surrounding air and the membrane were included in the model. The results show that nonlinearities and coupling phenomena have a considerable effect on the dynamic behaviour of the system. The nonlinearities cause a noticeable stiffening of the membrane, and the vibration frequency of nonlinear system increases as the amplitude grows. At high values of transport velocity the first mode frequency passes over the second linear harmonic, and even the third. The results also show that the cylindrical supports have a distinct influence on the behaviour of an axially moving sheet. The boundary of the contact region clearly moves and weakens the nonlinear hardening phenomena that otherwise increase the fundamental frequency. This influence strengthens as the radius of the cylinders increases.

Linear and nonlinear microwave properties of chemical vapor deposition (CVD)-grown graphene are characterized by incorporating a coplanar waveguide (CPW) transmission-line test structure. The intrinsic linear transport properties (S-parameters) of the graphene sample are measured and extracted via a deembedding procedure and then fitted with an equivalent circuit model up to 10 GHz. A statistical uncertainty analysis based on multiple measurements is implemented to esti- mate the error of the extracted graphene linear parameters as well. Nonlinear properties (second- and third-order harmonics as a function of fundamental input power) of the sample are also measured with a fundamental input signal of 1 GHz. Clear harmonics generated from graphene are observed, while no obvious fundamental power saturation is seen. The measured nonlinearity is applied in a graphene patch antenna case study to understand its influence on potential applications in terms of third-order intermodulation levels.

Numerous studies have documented the existence of nonlinearity within various financial time series. But how important of a finding is this? This dissertation examines this issue from a number of perspectives. First, is the nonlinearity that has been found a statistical anomaly that is isolated to a few of the more widely known financial time series or is nonlinearity a statistical regularity inherent in such series? Second, even if nonlinearity is pervasive, does this finding have any practical relevance for finance practitioners or academics? Using the relatively financially isolated but nonetheless well-traded Taiwan Stock Exchange as a case study, it is found that virtually all of the stocks trading on this exchange exhibit nonlinearity. The pervasiveness of nonlinearity within this market, combined with earlier results from other markets, suggests that nonlinearity is an inherent aspect of financial time series. Furthermore, closer examination of the time-paths of various measures of this nonlinearity via both windowed testing and recursive testing and parameter estimation reveals an additional complication, the possibility of nonstationarity. The serial dependency structures, especially for the nonlinear dependencies, do not appear to be constant, but instead appear to exhibit a number of brief episodes of extremely strong dependencies, followed by longer stretches of relatively quiet behavior. On average, though, these nonlinearities appear with sufficient strength to be significant for the full sample. Continuing on to examine the relevance of such nonlinearities for empirical work in finance, a variety of conditionally heteroskedastic models were fit to the returns for a subsample Taiwanese stocks, the Taiwanese stock index, and stock indices for other stock markets, including New York, London, Tokyo, Hong Kong, and Singapore. In a majority of cases, such models appear to be successful at filtering out the extant nonlinearity from these series of returns; however, a variety of indicators suggest that these models are not statistically well-specified for these returns, calling into question the inferences obtained from these models. Furthermore, a comparison of the various conditionally heteroskedastic models with each other and with a dynamic linear regression model reveals that, for many of the data series, the inferences obtained from these models regarding the day-of-the-week effect and the extant autocorrelation within the data varied from model to model. This finding suggests the importance of adequately accounting for nonlinear serial dependencies (and of ensuring data stationarity) when studying financial time series, even when other empirical aspects of the data are the focus of attention. / Ph. D.

In this dissertation, various analytical models to characterize fiber nonlinearities have been applied, and the ranges of validity of the models are determined by comparing with numerical results. First, the perturbation approach is used to solve the nonlinear Schrödinger equation, and its range of validity is determined by comparing to the split-step Fourier method. In addition, it is shown mathematically that the perturbation approach is equivalent to the Volterra series approach. Secondly, root-mean-square (RMS) widths both in the time domain and in the frequency domain are modeled. It is shown that there exists an optimal input pulse width to minimize output pulse width based on the derived RMS models, and the functional form of the minimum output pulse width is derived. The response of a fiber to a sinusoidally modulated input which models an alternating bit sequence is studied to see its utility in measuring system performance in the presence of the fiber nonlinearities. In a single channel system, the sinusoidal response shows a strong correlation with eye-opening penalty in the normal dispersion region over a wide range of parameters, but over a more limited range in the anomalous dispersion region. The cross-phase modulation (CPM) penalty in a multi-channel system is also studied using the sinusoidally modulated input signal. The derived expression shows good agreement with numerical results in conventional fiber systems over a wide range of channel spacing, ∆<i>f</i>, and in dispersion-shifted fiber systems when ∆<i>f</i> > 100GHz. It is also shown that the effect of fiber nonlinearities may be characterized with stochastic input signals using noise-loading analysis. In a dense wavelength division multiplexed (DWDM) system where channels are spaced very closely, the broadened spectrum due to various nonlinear effects like SPM (self-phase modulation), CPM, and FWM (four-wave mixing) is in practice indistinguishable. In such a system, the noise-loading analysis could be useful in assessing the effects of broadened spectrum due to fiber nonlinearities on system performance. Finally, it is shown numerically how fiber nonlinearities can be utilized to improve system performance of a spectrum-sliced WDM system. The major limiting factors of utilizing fiber nonlinearities are also discussed. / Ph. D.

Statistically significant prediction of stock price changes requires security returns' correlation with, or dependence upon, some variable(s) across time. Since a security's past return is commonly employed in forecasting, and because the lack of lower-order correlation does not guarantee higher-order independence, nonlinear testing that focuses on higher-order moments of stock return distributions may reveal exploitable stock return dependencies. This dissertation fits AR models to TAQ data sampled at ten-minute intervals for 20 small-capitalization, 20 mid-capitalization, and 20 large-capitalization NYSE securities, for the years 1993, 1995, 1997, 1999 and 2001. The Hinich Patterson Bicovariance statistic (to reveal nonlinear and linear autocorrelation) is computed for each of the 1243 trading days for each of the 60 securities. This statistic is examined to see if it is more or less likely to occur in securities with differing market capitalization, at various calendar periods, in conjunction with trading volume, or instances of changing investor sentiment, as evidenced by the put-call ratio. There is a statistically significant difference in the level and incidence of nonlinear behavior for the different-sized portfolios. Large-cap stocks exhibit the highest level and greatest incidence of nonlinear behavior, followed by mid-cap stocks, and then small-cap stocks. These differences are most pronounced at the beginning of decade and remain significant throughout the decade. For all size portfolios, nonlinear correlation increases throughout the decade, while linear correlation decreases. Statistical significance between the nonlinear or the linear test statistics and trading volume occur on a year-by-year basis only for small-cap stocks. There is sporadic seasonality significance for all portfolios over the decade, but only the small-cap portfolio consistently exhibits a notable "December effect". The average nonlinear statistic for small-cap stocks is larger in December than for other months of the year. The fourth quarter of the year for small-cap stocks also exhibits significantly higher levels of nonlinearity. An OLS regression of the put/call ratio to proxy for investor sentiment against the H and C statistic was run from October 1995 through December 2001. There are instances of sporadic correlations among the different portfolios, indicating this relationship is more dynamic than previously imagined. / Ph. D.

Reinforced concrete (RC) shear wall buildings constitute a significant portion of the building inventory in many earthquake-prone regions. A similar type of structural system is fully-grouted reinforced masonry (RM) shear wall structures. The accurate determination of the nonlinear response of reinforced concrete and reinforced masonry (RC/RM) walls subjected to lateral loading is of uttermost importance for ensuring the safety of the built environment. Analytical models provide a cost efficient and comprehensive tool to study the nonlinear response of RC/RM structures, as compared to experimental tests. Predictive models should capture nonlinear material behavior as well as the geometrically nonlinear response of RC/RM shear wall structures during major seismic events. This thesis outlines the formulation and validation of a nonlinear shell element for the simulation of RC/RM structures. The proposed shell element enhances an existing formulation of a four-node Discrete Kirchhoff shell element through the inclusion of a corotational approach to account for geometric nonlinearities and of nonlinear material models to capture the effect of cracking and crushing in concrete or masonry and the nonlinear hysteretic behavior of reinforcing steel. The analytical results obtained from multiple linear and nonlinear analyses are compared against theoretical solutions and experimental test data. These comparative validation studies show the enhanced shell element can satisfactorily capture the salient features of the response of nonlinear reinforced concrete/masonry shear wall structures including axial-shear-flexure interaction, damage patterns, and in-plane and out-of-plane loading. / Master of Science