The paper considers approximations of time-continuous epsilon-correlated random processes by interpolation of time-discrete Moving-Average processes. These approximations are helpful for Monte-Carlo simulations of the response of systems containing random parameters described by epsilon-correlated processes. The paper focuses on the approximation of stationary epsilon-correlated processes with a prescribed correlation function. Numerical results are presented.

In the paper we study sequences of random functions which are defined by some interpolation procedures for a given random function. We investigate the problem in what sense and under which conditions the sequences converge to the prescribed random function. Sufficient conditions for convergence of moment characteristics, of finite dimensional distributions and for weak convergence of distributions in spaces of continuous functions are given. The treatment of such questions is stimulated by an investigation of Monte Carlo simulation procedures for certain classes of random functions. In an appendix basic facts concerning weak convergence of probability measures in metric spaces are summarized.

The autocorrelation function is a basic tool for time series analysis. The clas- sical estimation is very sensitive to outliers and can lead to misleading results. This thesis deals with robust estimations of the autocorrelation function, which is more resistant to the outliers than the classical estimation. There are presen- ted following approaches: leaving out the outliers from the data, replacement the average with the median, data transformation, the estimation of another coeffici- ent, robust estimation of the partial autocorrelation function or linear regression. The thesis describes the applicability of the presented methods, their advantages and disadvantages and necessary assumptions. All the approaches are compared in simulation study and applied to real financial data. 1

Cold adaptation in stationary phase in Bacillus subtilis One of the most important abiotic factor which influences life of bacterial cells is the ambient temperature. A decrease of this temperature is usually accompanied usually with the loss of the fluidity of bacterial cytoplasmatic membrane. While the mechanisms of the responses to the cold shock during the exponential phase of growth are well known for Bacillus subtilis, the responses of stationary phase cells had not been studied yet (despite the stationary phase is the most common state of microorganism in the nature). There are two independent mechanisms which restores much needed fluidity in Bacillus subtilis - short-term adaptation and long-term adaptation. Short-term adaptation is based on the function of fatty acid desaturase coded by des gene. Long-term adaptation relies on the change in ratio of iso- and anteiso- branched fatty acids. In this work we examinated membrane adaptation during stationary phase under two different conditions, namely under cultivation at stable low temperature and after cold shock. The highest activity of Pdes was observed for cultivation at 25 řC and for the cold shock applied from cultivation in 37 řC to 25 řC. Anisotropy measurements and fatty acids analysis were also performed. Results indicated, that the...

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第18446号 / 理博第4006号 / 新制||理||1578(附属図書館) / 31324 / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)准教授 藤 定義, 教授 佐々 真一, 教授 早川 尚男 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第20517号 / 情博第645号 / 新制||情||111(附属図書館) / 京都大学大学院情報学研究科システム科学専攻 / (主査)教授 髙橋 豊, 教授 太田 快人, 教授 大塚 敏之, 准教授 増山 博之 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第21444号 / 理博第4437号 / 新制||理||1638(附属図書館) / 京都大学大学院理学研究科数学・数理解析専攻 / (主査)准教授 前川 泰則, 教授 上 正明, 教授 堤 誉志雄 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

Non-stationary signals, particularly frequency modulated (FM) signals which arecharacterized by their time-varying instantaneous frequencies (IFs), are fundamental to radar, sonar, radio astronomy, biomedical applications, image processing, speech processing, and wireless communications. Time-frequency (TF) analyses of such signals provide two-dimensional mapping of time-domain signals, and thus are regarded as the most preferred technique for detection, parameter estimation, analysis and utilization of such signals. In practice, these signals are often received with compressed measurements as a result of either missing samples, irregular samplings, or intentional under-sampling of the signals. These compressed measurements induce undesired noise-like artifacts in the TF representations (TFRs) of such signals. Compared to random missing data, burst missing samples present a more realistic, yet a more challenging, scenario for signal detection and parameter estimation through robust TFRs. In this dissertation, we investigated the effects of burst missing samples on different joint-variable domain representations in detail. Conventional TFRs are not designed to deal with such compressed observations. On the other hand, sparsity of such non-stationary signals in the TF domain facilitates utilization of sparse reconstruction-based methods. The limitations of conventional TF approaches and the sparsity of non-stationary signals in TF domain motivated us to develop effective TF analysis techniques that enable improved IF estimation of such signals with high resolution, mitigate undesired effects of cross terms and artifacts and achieve highly concentrated robust TFRs, which is the goal of this dissertation. In this dissertation, we developed several TF analysis techniques that achieved the aforementioned objectives. The developed methods are mainly classified into two three broad categories: iterative missing data recovery, adaptive local filtering based TF approach, and signal stationarization-based approaches. In the first category, we recovered the missing data in the instantaneous auto-correlation function (IAF) domain in conjunction with signal-adaptive TF kernels that are adopted to mitigate undesired cross-terms and preserve desired auto-terms. In these approaches, we took advantage of the fact that such non-stationary signals become stationary in the IAF domain at each time instant. In the second category, we developed a novel adaptive local filtering-based TF approach that involves local peak detection and filtering of TFRs within a window of a specified length at each time instant. The threshold for each local TF segment is adapted based on the local maximum values of the signal within that segment. This approach offers low-complexity, and is particularly useful for multi-component signals with distinct amplitude levels. Finally, we developed knowledge-based TFRs based on signal stationarization and demonstrated the effectiveness of the proposed TF techniques in high-resolution Doppler analysis of multipath over-the-horizon radar (OTHR) signals. This is an effective technique that enables improved target parameter estimation in OTHR operations. However, due to high proximity of these Doppler signatures in TF domain, their separation poses a challenging problem. By utilizing signal self-stationarization and ensuring IF continuity, the developed approaches show excellent performance to handle multiple signal components with variations in their amplitude levels. / Electrical and Computer Engineering

Ultrahigh pressure liquid chromatography (UHPLC) makes it possible to use very small particles (< 2 µm) as packing materials to provide high column efficiencies. Results from a careful comparison of small porous and nonporous particles show that when the particle size is small enough (< 2 µm), both porous and nonporous particles give excellent performance, and the differences in column efficiencies between porous and nonporous particles become insignificant. Columns packed with bare diamond particles could separate small molecules, especially polar molecules, however, severe tailing occurred for less polar compounds. The polybutadiene coated diamond particles gave greater retention and better separation of small molecules compared to bare particles, although no improvement in column efficiency was observed. Changes in surface bonding of thermally hydrogenated diamond particles was achieved by chemical modification using various organic peroxides with or without reagents containing long carbon chain functional groups. It appears that the alkyl groups were attached onto the diamond surface with limited coverage. LC experiments did not demonstrate good separation; however, changes in LC behavior were observed. A repetitive solvent programming approach was successfully applied to the analysis of a continuous sample stream in microbore LC. Each analysis cycle consisted of three steps: pseudo-injection, elution and rinse. In the pseudo-injection step, elution with a non- or poor-eluting solvent produced a concentrated sample plug due to on-column focusing. Factors influencing peak symmetry, resolution and analysis cycle length were investigated. Quantitative analysis of a continuous sample stream is possible under certain operating conditions. Electric field gradient focusing (EFGF) devices with distributed resistor substrates could focus proteins in the separation channel, however, the focused bands were not stable, and the repeatability was poor due to the formation of bubbles and pH gradient in the separation channel. Both fiber-based and porous glass capillary-based planar EFGF devices with changing cross-sectional area (CCSA) channels were constructed and evaluated with the aid of a home-made scanning laser-induced fluorescence detection system. The fiber-based CCSA EFGF devices gave poorer performance compared with glass capillary based devices. Porous glass capillary-based EFGF devices could focus single proteins and separate mixtures of two to three proteins.

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