Massive shales and fractures are the main cause of seismic anisotropy in the upper-most part of the crust, caused either by sedimentary or tectonic processes. Neglecting the effect of seismic anisotropy in seismic processing algorithms may incorrectly image the seismic reflectors. This will also influence the quantitative amplitude analysis such as the acoustic or elastic impedance inversion and amplitude versus offsets analysis. Therefore it is important to obtain anisotropy parameters from seismic data. Conventional layer stripping inversion schemes and reflector based reflectivity inversion methods are solely dependent upon a specific reflector, without considering the effect of the other layers. This, on one hand, does not take the effect of transmission in reflectivity inversion into the account, and on the other hand, ignores the information from the waves travelling toward the lower layers. I provide a framework to integrate the information for each specific layer from all the rays which have travelled across this layer. To estimate anisotropy parameters I have implemented unconstrained minimization algorithms such as nonlinear conjugate gradients and variable metric methods, I also provide a nonlinear least square method, based on the Levenberg-Marquardt algorithm. In a stack of horizontal transversely isotropic layers with vertical axis of symmetry, where the layer properties are laterally invariant, we provide two different inversion schemes; traveltime and waveform inversion. / Both inversion schemes utilize compressional and joint compressional and converted shear waves. A new exact traveltime equation has been formulated for a dipping transversely isotropic system of layers. These traveltimes are also parametrized by the ray parameters for each ray element. I use the Newton method of minimization to estimate the ray parameter using a random prior model from a uniform distribution. Numerical results show that with the assumption of weak anisotropy, Thomsen’s anisotropy parameters can be estimated with a high accuracy. The inversion algorithms have been implemented as a software package in a C++ object oriented environment.

A wavelet is a function which is used to construct a specific type of orthonormal basis. We are interested in using C*-algebras and Hilbert C*-modules to study wavelets. A Hilbert C*-module is a generalisation of a Hilbert space for which the inner product takes its values in a C*-algebra instead of the complex numbers. We study wavelets in an arbitrary Hilbert space and construct some Hilbert C*-modules over a group C*-algebra which will be used to study the properties of wavelets. We study wavelets by constructing Hilbert C*-modules over C*-algebras generated by groups of translations. We shall examine how this construction works in both the Fourier and non-Fourier domains. We also make use of Hilbert C*-modules over the space of essentially bounded functions on tori. We shall use the Hilbert C*-modules mentioned above to study wavelet and scaling filters, the fast wavelet transform, and the cascade algorithm. We shall furthermore use Hilbert C*-modules over matrix C*-algebras to study multiwavelets.

<p>In this thesis, a two-dimensional pixel-wise deconvolution method for partial volume correction (PVC) for combined Positron Emission Tomography and Computer Tomography (PET/CT) imaging has been developed. The method is based on Van Cittert's deconvolution algorithm and includes a noise reduction method based on adaptive smoothing and median filters. Furthermore, a technique to take into account the position dependent PET point spread function (PSF) and to reduce ringing artifacts is also described. The quantitative and qualitative performance of the proposed PVC algorithm was evaluated using phantom experiments with varying object size, background and noise level. PVC results in an increased activity recovery as well as image contrast enhancement. However, the quantitative performance of the algorithm is impaired by the presence of background activity and image noise. When applying the correction on clinical PET images, the result was an increase in standardized uptake values, up to 98% for small tumors in the lung. These results suggest that the PVC described in this work significantly improves activity recovery without producing excessive amount of ringing artifacts and noise amplification. The main limitations of the algorithm are the restriction to two dimensions and the lack of regularization constraints based on anatomical information from the co-registered CT images.</p>

<p>An automatic road toll system enables the passing vehicles to change lanes and no stop is needed for payment. Because of different weight of personal cars, busses, lorries (trucks) and other vehicles, they affect the road in different ways. It is of interest to categorize the vehicles into different classes depending of their weight so that the right fee can be set. An automatic road toll system developed by Combitech Traffic Systems AB (now Kapsch TrafficCom AB), Joenkoping, Sweden, classifies the vehicles with help of a so called height image. This is a three dimensional image produced by two photographs of a vehicle. The photographs displays the same view but are mounted with a little spacing. This spacing makes it possible to create a height image. The existing classification uses only length, width and height to divide vehicles into classes. Vehicles of the same dimensions would then belong to the same class independent of their weight. An important example is busses and lorries (trucks) which often have the same dimensions, but trucks often have greater weight and should therefore require a larger fee. This work describes methods for separating busses from lorries with the help of height images. The methods search for variations in the width and height, and other features specific for busses and lorries respectively.</p>

<p>The main issue in this thesis is to minimize the number of operations and the energy consumption per operation for the computation (arithmetic operation) part of DSP circuits, such as Finite Impulse Response Filters (FIR), Discrete Cosine Transform (DCT), and Discrete Fourier Transform (DFT) etc. More specific, the focus is on the elimination of most frequent common sub-expression (CSE) in binary, Canonic Sign Digit (CSD), Twos Complement or Sign Digit representation of the coefficients of non-recursive multiple input multiple output (MIMO)  FIR system , which can be realized using shift-and-add based operations only. The possibilities to reduce the complexity i.e. the chip area, and the energy consumption have been investigated.</p><p>We have proposed an algorithm which finds the most common sub expression in the binary/CSD/Twos Complement/Sign Digit representation of coefficients of non-recursive MIMO multiplier less FIR systems. We have implemented the algorithm in MATLAB. Also we have proposed different tie-breakers for the selection of most frequent common sub-expression, which will affect the complexity (Area and Power consumption) of the overall system. One choice (tie breaker) is to select the pattern (if there is a tie for the most frequent pattern) which will result in minimum number of delay elements and hence the area of the overall system will be reduced. Another tie-breaker is to choose the pattern which will result in minimum adder depth (the number of cascaded adders). Minimum adder depth will result in least number of glitches which is the main factor for the power consumption in MIMO multiplier less FIR systems. Switching activity will be increased when glitches are propagated to subsequent adders (which occur if adder depth is high). As the power consumption is proportional to the switching activity (glitches) hence we will use the sub-expression which will result in lowest adder depth for the overall system.</p>

<p>We study the problem of list decoding with focus on the case when we have a list size limited to two. Under this restriction we derive general lower bounds on the maximum possible size of a list-of-2-decodable code. We study the set of correctable error patterns in an attempt to obtain a characterization. For a special family of Reed-Solomon codes - which we identify and name 'class-I codes' - we give a weight-based characterization of the correctable error patterns under list-of-2 decoding. As a tool in this analysis we use the theoretical framework of Sudan's algorithm. The characterization is used in an exact calculation of the probability of transmission error in the symmetric channel when list-of-2 decoding is used. The results from the analysis and complementary simulations for QAM-systems show that a list-of-2 decoding gain of nearly 1 dB can be achieved.</p><p>Further we study Sudan's algorithm for list decoding of Reed-Solomon codes for the special case of the class-I codes. For these codes algorithms are suggested for both the first and second step of Sudan's algorithm. Hardware solutions for both steps based on the derived algorithms are presented.</p>

<p>It is important to detect faults in bus details at an early stage. Because the driving style affects the breakdown of different details in the bus, identification of the driving style is important to minimize the number of failures in buses.</p><p>The identification of the driving style of the driver was based on the input data which contained examples of the driving runs of each class. K-nearest neighbor and neural networks algorithms were used. Different models were tested.</p><p>It was shown that the results depend on the selected driving runs. A hypothesis was suggested that the examples from different driving runs have different parameters which affect the results of the classification.</p><p>The best results were achieved by using a subset of variables chosen with help of the forward feature selection procedure. The percent of correct classifications is about 89-90 % for the k-nearest neighbor algorithm and 88-93 % for the neural networks.</p><p>Feature selection allowed a significant improvement in the results of the k-nearest neighbor algorithm and in the results of the neural networks algorithm received for the case when the training and testing data sets were selected from the different driving runs. On the other hand, feature selection did not affect the results received with the neural networks for the case when the training and testing data sets were selected from the same driving runs.</p><p>Another way to improve the results is to use smoothing. Computing the average class among a number of consequent examples allowed achieving a decrease in the error.</p>

<p>Ultra wideband (UWB) communication systems refers to systems whose bandwidth is many times greater than the “narrowband” systems (refers to a signal which occupies only small amount of space on the radio spectrum). UWB can be used for indoor, communications for high data rates, or very low data rates for substantial link distances because of the extremely large bandwidth, immune to multi-path fading, penetrations through concrete block or obstacles. UWB can also used for short distance ranging whose applications include asset location in a warehouse, position location for wireless sensor networks, and collision avoidance.</p><p>In order to verify analytical and simulation results with real-world measurements, the need for experimental UWB systems arises. The Institute of Communications Engineering [IANT] has developed a low-cost experimental UWB positioning system to test UWB based positioning concepts. The mobile devices use the avalanche effect of transistors for simple generation of bi-phase pulses and are TDMA multi-user capable. The receiver is implemented in software and employs coherent cross-correlation with peak detection to localize the mobile unit via Time-Difference-Of-Arrival (TDOA) algorithms. Since the power of a proposed UWB system’s signal spread over a very wide bandwidth, the frequencies allocated to multiple existing narrowband systems may interfere with UWB spectrum. The goal of the filters discussed in this project is to cancel or suppress the interference while not distort the desired signal. To investigate the interference, we develop a algorithm to calculate the interference tones. In this thesis, we assume the interference to be narrowband interference (NBI) modeled as sinusoidal tones with unknown amplitude, frequency and phase. If we known the interference tones then it may be removed using a simple notched filter. Herein, we chose an adaptive filter so that it can adjust the interference tone automatically and cancel. In this thesis I tested adaptive filter technique to cancel interference cancellation (ie) LMS algorithm and Adaptive Noise Cancellation (ANC) technique. In this thesis performance of the both filters are compared.</p>

No description available.

<p>Inferring phylogeny is a difficult computational problem. Heuristics are necessary to minimize the time spent evaluating non optimal trees. In paper I, we developed an approach for heuristic searching, using a genetic algorithm. Genetic algorithms mimic the natural selections ability to solve complex problems. The algorithm can reduce the time required for weighted maximum parsimony phylogenetic inference using protein sequences, especially for data sets involving large number of taxa. </p><p>Evaluating and comparing the ability of phylogenetic methods to infer the correct topology is complex. In paper II, we developed software that determines the minimum subtree prune and regraft (SPR) distance between binary trees to ease the process. The minimum SPR distance can be used to measure the incongruence between trees inferred using different methods. Given a known topology the methods could be evaluated on their ability to infer the correct phylogeny given specific data. </p><p>The minimum SPR software the intermediate trees that separate two binary trees. In paper III we developed software that given a set of incongruent trees determines the median SPR consensus tree i.e. the tree that explains the trees with a minimum of SPR operations. We investigated the median SPR consensus tree and its possible interpretation as a species tree given a set of gene trees. We used a set of α-proteobacteria gene trees to test the ability of the algorithm to infer a species tree and compared it to previous studies. The results show that the algorithm can successfully reconstruct a species tree.</p><p>Expressed sequence tag (EST) data is important in determining intron-exon boundaries, single nucleotide polymorphism and the coding sequence of genes. In paper IV we aligned ESTs to the genome to evaluate the quality of EST data. The results show that many ESTs are contaminated by vector sequences and low quality regions. The reliability of EST data is largely determined by the clustering of the ESTs and the association of the clusters to the correct portion of genome. We investigate the performance of EST clustering using the genome as template compared to previously existing methods using pair-wise alignments. The results show that using the genome as guidance improves the resulting EST clusters in respect to the extent ESTs originating from the same transcriptional unit are separated into disjunct clusters. </p>