Eine klassische Art, die Dynamik nichtlinearer Systeme zu beschreiben, besteht in der Analyse ihrer Fourierspektren. Für periodische und quasiperiodische Prozesse besteht das Fourierspektrum nur aus diskreten Deltafunktionen. Das Spektrum einer chaotischen Bewegung ist hingegen durch das Vorhandensein einer stetigen Komponente gekennzeichnet. In der Arbeit geht es um einen eigenartigen, weder regulären noch vollständig chaotischen Zustand mit sogenanntem singulärstetigen Leistungsspektrum. <br /> Unsere Analyse ergab verschiedene Fälle aus weit auseinanderliegenden Gebieten, in denen singulär stetige (fraktale) Spektren auftreten. Die Beispiele betreffen sowohl physikalische Prozesse, die auf iterierte diskrete Abbildungen oder gar symbolische Sequenzen reduzierbar sind, wie auch Prozesse, deren Beschreibung auf den gewöhnlichen oder partiellen Differentialgleichungen basiert. / One of the classical ways to describe the dynamics of nonlinear systems is to analyze theur Fourier spectra. For periodic and quasiperiodic processes the Fourier spectrum consists purely of discrete delta-functions. On the contrary, the spectrum of a chaotic motion is marked by the presence of the continuous component. In this work, we describe the peculiar, neither regular nor completely chaotic state with so called singular-continuous power spectrum. <br /> Our investigations concern various cases from most different fields, where one meets the singular continuous (fractal) spectra. The examples include both the physical processes which can be reduced to iterated discrete mappings or even symbolic sequences, and the processes whose description is based on the ordinary or partial differential equations.

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Wetlands are nominally characterized by, vegetation, presence of saturated soils and/or period and depth of standing water (inundation). Wetland hydroperiod, traditionally defined by the period or duration of inundation, is considered to control the ecological function and resultant plant community. This study seeks to redefine "hydroperiod" to incorporate both surface and subsurface water-level fluctuations, to identify predominant hydroperiod of different wetland types, and to find the range of the water-level fluctuations during the predominant hydroperiod durations. The motivation being that wetland ecological condition is controlled not just by the period of inundation but also by the proximity and depth to water-table and period of water-level fluctuation. To accomplish this, a frequency distribution analysis of water-table and stage levels in wetlands is performed. The conclusions of this study suggest a need to rethink current definitions and methodologies in determining hydroperiod. Redefining wetland hydroperiod taking into consideration depth to water-table, namely water-level periods and depths below ground surface, may also aid in the understanding of how fluctuations in water-levels in a wetland affect plant ecology.

During the last decade, the transit method has evolved to one of the most promising techniques in the search for extrasolar planets and the quest to find other earth-like worlds. In theory, the transit method is straight forward being based on the detection of an apparent dimming of the host star’s light due to an orbiting planet traversing in front of the observer. However, in practice, the detection of such light curve dips and their confident ascription to a planetary transit is heavily burdened by the presence of different sources of noise, the most prominent of which is probably the so called intrinsic stellar variability. Filtering out potential transit signals from background noise requires a well adjusted high-pass filter. In order to optimize such a filter, i.e. to achieve best separation between signal and noise, one typically requires access to benchmark datasets that exhibit the same light curve with and without obstructing noise. Several methods for simulating stellar variability have been proposed for the construction of such benchmark datasets. However, while such methods have been widely used in testing transit method detection algorithms in the past, it is not very well known how such simulations compare to real recorded light curves - a fact that might be contributed to the lack of large databases of stellar light curves for comparisons at that time. With the increasing amount of light curve data now available due to missions such as Kepler, I have here undertaken such a comparison of synthetic and real light curves for one particular method that simulates stellar variability based on scaled power spectra of the Sun’s flux variations. Conducting the respective comparison also in terms of estimated power spectra of real and simulated light curves, I have revealed that the two datasets exhibit substantial differences in average power, with the synthetic power spectra having generally a lower power and also lacking certain distinct power peaks present in the real light curves. The results of this study suggest that scaled power spectra of solar variability alone might be insufficient for light curve simulations and that more work will be required to understand the origin and relevance of the observed power peaks in order to improve on such light curve models.

Digital radiography systems are important diagnostic tools for modern medicine. The images are produced when x-ray sensitive materials are coupled directly onto the sensing element of the detector panels. As a result, the size of the detector panels is the same size as the x-ray image. An alternative to the modern DR system is to image the x-ray phosphor screen with a lens onto a digital camera. Potential advantages of this approach include rapid readout, flexible magnification and field of view depending on applications. We have evaluated lens-coupled DR systems for the task of signal detection by analyzing the covariance matrix of the images for three cases, using a perfect detector and lens, when images are affected by blurring due to the lens and screen, and for a signal embedded in a complex random background. We compared the performance of lens-coupled DR systems using three types of digital cameras. These include a scientific CCD, a scientific CMOS, and a prosumer DSLR camera. We found that both the prosumer DSLR and the scientific CMOS have lower noise than the scientific CCD camera by looking at their noise power spectrum. We have built two portable low-cost DR systems, which were used in the field in Nepal and Utah. We have also constructed a lens-coupled CT system, which included a calibration routine and an iterative reconstruction algorithm written in CUDA.

Approved for public release; distribution is unlimited / Capacitance and conductance measurements using two and four wire techniques were developed and statically and dynamically calibrated in this thesis. The voltage sensitivities range from 7.3 to 8.1 ± 0.1 mV/cm for the two wire capacitance system static calibrations. This is ± 5.2% of the limiting theoretical value. The voltage sensitivities range from 0.3 to 0.4 ± 0.1 V/cm for the four wire conductance system static calibrations. Dynamic calibrations were only completed for the conductance system. The dynamic calibration results were weakly frequency dependent with a qj-0.15 decay in a limited, 2-4 Hz range. Wind power spectrum measurements were taken in the existing Upper Ocean Simulations Facility at the Naval Postgraduate School. There was excellent agreement in the spectra with both techniques. Driven gravity wave frequency downshifting and wind energy dumping was observed in the combined gravity wave and wind-wave measurements. The power spectra peaked near two Hertz and decayed at 50 to 70 dB per decade, or as CO -5 to G)" 7 for both systems. Gravity wave phase speed and wavelength measurements were performed with the capacitance system. The results were approximately 40% higher than theory. / http://archive.org/details/developmentcalib00yarb

To provide a basis for electroencephalography (EEG) neurofeedback protocols for bulimianervosa (BN), binge-eating disorder (BED), and obesity, this systematic review investigates alterations in EEG-measured brain activity, specifically frequency bands. A systematic literature search with pre-defined search terms yielded N = 7 studies meeting the inclusion criteria. The risk of bias was assessed for all studies. In resting-state EEG, the beta activity was elevated in fronto-central regions in individuals with obesity and comorbid BED. In food-cue conditions, both obese individuals with and without BED showed increased beta activity, suggesting increased awareness of food cues and a heightened attentional focus towards food stimuli. The level of beta activity was positively correlated with eating disorder psychopathology in resting and food-cue conditions. In individuals with BN, there was no evidence for altered EEG spectral power. The results indicate specific alterations in EEGbased brain activity in individuals with BED and obesity. More high-quality studies are needed to further confirm these findings and to transfer them into EEG-based interventions.

This paper demonstrates the implementation of R-CNN in terms of electromyography-related signals to recognize hand gestures. The signal acquisition is implemented using electrodes situated on the forearm, and the biomedical signals are generated to perform the signals preprocessing using wavelet packet transform to perform the feature extraction. The R-CNN methodology is used to map the specific features that are acquired from the wavelet power spectrum to validate and train how the architecture is framed. Additionally, the real-time test is completed to reach the accuracy of 96.48% compared to the related methods. This kind of result proves that the proposed work has the highest amount of accuracy in recognizing the gestures.

The standard L2B ocean wind product from the Advanced Scatterometer (ASCAT) is retrieved as a 25 km product on a 12.5 km grid. Ultra-high resolution (UHR) processing allows ASCAT wind retrieval on a high-resolution 1.25 km grid. Ideally, such a high-resolution sample grid provides wind information down to a 2.5 km scale, allowing better analysis of winds with high spatial variability such as those in near-coastal regions and storms. Though the wind field is sampled on a finer grid, the actual data resolution needs to be validated. This thesis provides an analysis and validation of ASCAT UHR wind estimates in order to determine the improvement in resolution compared to the L2B product. This is done using analysis tools such as statistics, the power spectrum, and derivative fields, and through comparison to other high-resolution data such as synthetic aperture radar (SAR). The improvement of UHR wind retrieval is also explored by reducing ambiguity selection errors and correcting for contamination of wind vectors near land. Results confirm that ASCAT UHR winds contain high-resolution information that is not present in the L2B product. The resolution improvement is difficult to quantify due to a lack of truth data. Nevertheless, there is evidence to suggest that the resolution is improved by at least a factor of three to 10 km, and perhaps down to 3 or 4 km. It is found through comparison of UHR and SAR winds that (1) both products have common fine-scale features, (2) their comparative statistics are similar to that of L2B and SAR, suggesting that the high resolution content agrees just as well as the low resolution content because the comparison is performed at a finer scale (3) both products have derivative fields that match well, (4) the UHR product benefits from high-resolution direction information, and (5) the UHR product matches better the expected spectral properties of ocean winds. For the UHR processing improvement methods, the model-based improvement of UHR ambiguity selection allows obvious ambiguity errors to be found and corrected, increases the self-consistency of the wind field, and causes the spectrum to better follow a power law at high wavenumbers. The removal of land-contamination from near-coastal wind vectors allows accurate wind retrieval much closer to land and greater visibility of high-resolution wind features near the coast.

Since the characterization of the eye's monochromatic aberration fluctuations in 2001, the power spectrum has remained the most widely used method for analyzing their dynamics. However, the power spectrum does not capture the complexities of the fluctuations. We measured the monochromatic aberration dynamics of six subjects using a Shack-Hartmann sensor sampling at 21 Hz. We characterized the dynamics using techniques from chaos theory. We found that the attractor embedding dimension for all aberrations, for all subjects, was equal to three. The embedding lag averaged across aberrations and subjects was 0.31 +/- 0.07 s. The Lyapunov exponent of the rms wavefront error was positive for each subject, with an average value of 0.44 +/- 0.15 microm/s. This indicates that the aberration dynamics are chaotic. Implications for future modeling are discussed.