Purpose. Low-dose computed tomography is an important imaging modality for screening and surveillance of lung cancer. The goal of this study was to determine the extent to which dose could be minimized while maintaining diagnostic accuracy through knowledgeable selection of reconstruction techniques. Methods. An anthropomorphic phantom was imaged on a 320-slice volumetric CT scanner. Detectability of small solid lung nodules was evaluated as a function of dose, patient size, reconstruction filter and slice thickness by means of 9-alternative forced-choice observer tests. Results. Nodule detectability decreased sharply below a threshold dose level due to increased image noise. For large body habitus, optimal (smooth) filter selection reduced dose by a factor of ~3. Nodule detectability decreased for slice thicknesses larger than the nodule diameter. Conclusions. Radiation dose can be reduced well below current clinical protocols. Smooth reconstruction filters and avoidance of large slice thickness permits lower-dose techniques without tradeoff in diagnostic performance.

Purpose. Low-dose computed tomography is an important imaging modality for screening and surveillance of lung cancer. The goal of this study was to determine the extent to which dose could be minimized while maintaining diagnostic accuracy through knowledgeable selection of reconstruction techniques. Methods. An anthropomorphic phantom was imaged on a 320-slice volumetric CT scanner. Detectability of small solid lung nodules was evaluated as a function of dose, patient size, reconstruction filter and slice thickness by means of 9-alternative forced-choice observer tests. Results. Nodule detectability decreased sharply below a threshold dose level due to increased image noise. For large body habitus, optimal (smooth) filter selection reduced dose by a factor of ~3. Nodule detectability decreased for slice thicknesses larger than the nodule diameter. Conclusions. Radiation dose can be reduced well below current clinical protocols. Smooth reconstruction filters and avoidance of large slice thickness permits lower-dose techniques without tradeoff in diagnostic performance.

The combined observations of a planet’s transits and the radial velocity variations of its host star allow the determination of the planet’s orbital parameters, and most inter- estingly of its radius and mass, and hence its mean density. Observed densities provide important constraints to planet structure and evolution models. The uncertainties on the parameters of large exoplanets mainly arise from those on stellar masses and radii. For small exoplanets, the treatment of stellar variability limits the accuracy on the de- rived parameters. The goal of this PhD thesis was to reduce these sources of uncertainty by developing new techniques for stellar variability filtering and for the determination of stellar temperatures, and by robustly fitting the transits taking into account external constraints on the planet’s host star. To this end, I developed the Iterative Reconstruction Filter (IRF), a new post-detection stellar variability filter. By exploiting the prior knowledge of the planet’s orbital period, it simultaneously estimates the transit signal and the stellar variability signal, using a com- bination of moving average and median filters. The IRF was tested on simulated CoRoT light curves, where it significantly improved the estimate of the transit signal, particu- lary in the case of light curves with strong stellar variability. It was then applied to the light curves of the first seven planets discovered by CoRoT, a space mission designed to search for planetary transits, to obtain refined estimates of their parameters. As the IRF preserves all signal at the planet’s orbital period, t can also be used to search for secondary eclipses and orbital phase variations for the most promising cases. This en- abled the detection of the secondary eclipses of CoRoT-1b and CoRoT-2b in the white (300–1000 nm) CoRoT bandpass, as well as a marginal detection of CoRoT-1b’s orbital phase variations. The wide optical bandpass of CoRoT limits the distinction between thermal emission and reflected light contributions to the secondary eclipse. I developed a method to derive precise stellar relative temperatures using equiv- alent width ratios and applied it to the host stars of the first eight CoRoT planets. For stars with temperature within the calibrated range, the derived temperatures are con- sistent with the literature, but have smaller formal uncertainties. I then used a Markov Chain Monte Carlo technique to explore the correlations between planet parameters derived from transits, and the impact of external constraints (e.g. the spectroscopically derived stellar temperature, which is linked to the stellar density). Globally, this PhD thesis highlights, and in part addresses, the complexity of perform- ing detailed characterisation of transit light curves. Many low amplitude effects must be taken into account: residual stellar activity and systematics, stellar limb darkening, and the interplay of all available constraints on transit fitting. Several promising areas for further improvements and applications were identified. Current and future high precision photometry missions will discover increasing numbers of small planets around relatively active stars, and the IRF is expected to be useful in characterising them.

Maschinelle Beatmung kann neben den gewünschten Effekten eine vorbestehende Lungenerkrankung weiter aggravieren und sogar das Lungenparenchym zuvor lungengesunder Patienten schädigen. Mit Hilfe der quantitativen Computertomographie (qCT) können pathologische Belüftungszustände und gegebenenfalls durch maschinelle Beatmung verursachte Schäden analysiert werden. Solche auf der qCT basierende Analysen der Lungenbelüftung werden jedoch potentiell durch CT-Akquisitions- und Bildrekonstruktionsparameter beeinflusst. Um die Ergebnisse vor allem von Analysen des überbelüfteten Lungenvolumens richtig bewerten zu können, müssen solche Einflüsse untersucht werden. Bei 10 Versuchstieren (Schweine) wurden bei einem konstanten Atemwegsdruck von 25 cm H2O zuerst bei gesunder Lunge und dann erneut nach experimenteller Lungenschädigung CT-Bildserien mit zwei unterschiedlichen Strahlendosen angefertigt. Von diesen Rohdaten wurden Bildserien mit unterschiedlichen Rekonstruktionsparametern angefertigt und in jeder dieser Bildserien das überbelüftete Lungenvolumen bestimmt. Sowohl die Schichtdicke, der Filter als auch die Stromstärke hatten einen signifikanten Einfluss auf das eigentlich konstante überbelüftete Lungenvolumen, der jedoch nur teilweise klinisch relevant war. Bei der Interpretation von Messungen des überbelüfteten Lungenvolumens sollten dennoch die Einflüsse der genannten Parameter beachtet und für Vergleichsuntersuchungen gleiche Parametereinstellungen verwendet werden. Eine Dosisreduktion scheint dabei für Messungen des überbelüfteten Lungenvolumens praktikabel.

The presented work deals with the issue of digital mixing console. The main focus is on the design of sub-circuits for the digital mixer and the construction into the 19 "rack unit. The thesis presents a detailed description of individual parts and their use. Thesis also includes complete device designs, including a power supply and additional circuits.

The aim of the project is to design a concept of function generator with digital synthesis. The device will be controlled using microprocessor which allows synthesizing basic functions (sin, square, raw) as well as arbitrary functions stored in memory. User friendly graphical interface will be controlled by keyboard and rotary switch (IRC). The work emphasizes correct selection of DDS clock source, circuit elements and proper application of signal filtration method with attention to low distortion and low output phase noise.

This thesis deals with problematics of direct frequency digital synthesis. Principle and basic characteristics of this method of signal generating are explained in the introduction. It considers impact on purity of spectrum of output signal. Next chapter considers conception of the generator, namely choice of DDFS circuit and other basic blocks. Design of frequency multiplier, reconstruction filter and power amplifier are included. It also deals with choice of control circuit. The device is controlled by computer through USB. There was created user programme for this purpose. Measured characteristics are stated at the end of the work. This work includes schemes of connetions of designed parts including simulations and measured parameters.

The subject of this thesis is design and construction of a periodic signal generator prototype. The generator will use Atmel XMEGA128A4U microcontroller with computer control managed via USB interface. The thesis contains general solutions to the problem of generating signals with a special focus on utilization of DA converter – digital synthesis and reconstruction of the signal from DA converter output to continuous signal. The thesis further deals with implementation of the USB layer using two libraries (LUFA library on microcontroller side and LubUsbDotNet library on computer side). The final solution will include DC step-up converter for signal peak amplitude assessment and summing amplifier for adding the DC voltage to the output signal. The application will allow for generating signals of various shapes including user-defined ones. These signals will be displayed in the actual application window. There, users will be allowed to create user-defined signal in easy-to-use GUI or load it directly from a file.

Software radios (SWR) have been proposed for wireless communication systems to enable them to operate according to incompatible wireless communication standards by implementing most analog functions in the digital section on software-reprogrammable hardware. However, this significantly increases the required computations for SWR functionality, mainly because of the digital front-end computationally intensive filtering functions, such as sample rate conversion (SRC), channelization, and equalization. For increasing the computational efficiency of SWR systems, two new SRC methods with better performance than conventional SRC methods are presented. In the first SRC method, we modify the conventional CIC filters to enable them to perform SRC on slightly oversampled signals efficiently. We also describe a SRC method with high efficiency for SRC by factors greater than unity at which SRC in SWR systems may be computationally demanding. This SRC method efficiently increases the sample rate of wideband signals, especially in SWR base station transmitters, by applying Lagrange interpolation for evaluating output samples hierarchically using a low-rate signal that is computed with low cost from the input signal. A new channelizer/synthesizer is also developed for extracting/combining frequency multiplexed channels in SWR transceivers. The efficiency of this channelizer/synthesizer, which uses modulated perfect reconstruction (PR) filter banks, is higher than polyphase filter banks (when applicable) for processing few channels, and significantly higher than discrete filter banks for processing any number of variable-bandwidth channels where polyphase filter banks are inapplicable. Because the available methods for designing modulated PR filter banks are inapplicable due to the required number of subchannels and stopband attenuation of the prototype filters, a new design method for these filter banks is introduced. This method is reliable and significantly faster than the existing methods. Modulated PR filter banks are also considered for implementing a frequency-domain block blind equalizer capable of equalizing SWR signals transmitted though channels with long impulse responses and severe intersymbol interference (ISI). This blind equalizer adapts by using separate sets of weights to correct for the magnitude and phase distortion of the channel. The adaptation of this blind equalizer is significantly more reliable and its computational requirements increase at a lower rate compared to conventional time-domain equalizers making it efficient for equalizing long channels that exhibit severe ISI.

In system identification scenario, the linear approximation of the system modelled by its impulse response, is estimated in real time by gradient type Least Mean Square (LMS) or Recursive Least Squares (RLS) algorithms. In recent applications like acoustic echo cancellation, the order of the impulse response to be estimated is very high, and these traditional approaches are inefficient and real time implementation becomes difficult. Alternatively, the system is modelled by a set of shorter adaptive filters operating in parallel on subsampled signals. This approach, referred to as subband adaptive filtering, is expected to reduce not only the computational complexity but also to improve the convergence rate of the adaptive algorithm. But in practice, different subband adaptive algorithms have to be used to enhance the performance with respect to complexity, convergence rate and processing delay. A single subband adaptive filtering algorithm which outperforms the full band scheme in all applications is yet to be realized. This thesis is intended to study the subband adaptive filtering techniques and explore the possibilities of better algorithms for performance improvement. Three different subband adaptive algorithms have been proposed and their performance have been verified through simulations. These algorithms have been applied to acoustic echo cancellation and EEG artefact minimization problems. Details of the work To start with, the fast FIR filtering scheme introduced by Mou and Duhamel has been generalized. The Perfect Reconstruction Filter Bank (PRFB) is used to model the linear FIR system. The structure offers efficient implementation with reduced arithmetic complexity. By using a PRFB with non adjacent filters non overlapping, many channel filters can be eliminated from the structure. This helps in reducing the complexity of the structure further, but introduces approximation in the model. The modelling error depends on the stop band attenuation of the filters of the PRFB. The error introduced due to approximation is tolerable for applications like acoustic echo cancellation. The filtered output of the modified generalized fast filtering structure is given by (formula) where, Pk(z) is the main channel output, Pk,, k+1 (z) is the output of auxiliary channel filters at the reduced rate, Gk (z) is the kth synthesis filter and M the number of channels in the PRFB. An adaptation scheme is developed for adapting the main channel filters. Auxiliary channel filters are derived from main channel filters. Secondly, the aliasing problem of the classical structure is reduced without using the cross filters. Aliasing components in the estimated signal results in very poor steady state performance in the classical structure. Attempts to eliminate the aliasing have reduced the computation gain margin and the convergence rate. Any attempt to estimate the subband reference signals from the aliased subband input signals results in aliasing. The analysis filter Hk(z) having the following antialiasing property (formula) can avoid aliasing in the input subband signal. The asymmetry of the frequency response prevents the use of real analysis filters. In the investigation presented in this thesis, complex analysis filters and real'synthesis filters are used in the classical structure, to reduce the aliasing errors and to achieve superior convergence rate. PRFB is traditionally used in implementing Interpolated FIR (IFIR) structure. These filters may not be ideal for processing an input signal for an adaptive algorithm. As third contribution, the IFIR structure is modified using discrete finite frames. The model of an FIR filter s is given by Fc, with c = Hs. The columns of the matrix F forms a frame with rows of H as its dual frame. The matrix elements can be arbitrary except that the transformation should be implementable as a filter bank. This freedom is used to optimize the filter bank, with the knowledge of the input statistics, for initial convergence rate enhancement . Next, the proposed subband adaptive algorithms are applied to acoustic echo cancellation problem with realistic parameters. Speech input and sufficiently long Room Impulse Response (RIR) are used in the simulations. The Echo Return Loss Enhancement (ERLE)and the steady state error spectrum are used as performance measures to compare these algorithms with the full band scheme and other representative subband implementations. Finally, Subband adaptive algorithm is used in minimization of EOG (Electrooculogram) artefacts from measured EEG (Electroencephalogram) signal. An IIR filterbank providing sufficient isolation between the frequency bands is used in the modified IFIR structure and this structure has been employed in the artefact minimization scheme. The estimation error in the high frequency range has been reduced and the output signal to noise ratio has been increased by a couple of dB over that of the fullband scheme. Conclusions Efforts to find elegant Subband adaptive filtering algorithms will continue in the future. However, in this thesis, the generalized filtering algorithm could offer gain in filtering complexity of the order of M/2 and reduced misadjustment . The complex classical scheme offered improved convergence rate, reduced misadjustment and computational gains of the order of M/4 . The modifications of the IFIR structure using discrete finite frames made it possible to eliminate the processing delay and enhance the convergence rate. Typical performance of the complex classical case for speech input in a realistic scenario (8 channel case), offers ERLE of more than 45dB. The subband approach to EOG artefact minimization in EEG signal was found to be superior to their fullband counterpart. (Refer PDF file for Formulas)