Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

Modeling and Analysis of Some Heavy Tailed Time Series

The thesis has covered various aspects of modeling and analysis of finite mean time series with symmetric stable distributed innovations. Time series analysis based on Box and Jenkins methods are the most popular approaches where the models are linear and errors are Gaussian. We highlighted the limitations of classical time series analysis tools and explored some generalized tools and organized the approach parallel to the classical set up. In the present thesis we mainly studied the estimation and prediction of signal plus noise model. Here we assumed the signal and noise follow some models with symmetric stable innovations.We start the thesis with some motivating examples and application areas of alpha stable time series models. Classical time series analysis and corresponding theories based on finite variance models are extensively discussed in second chapter. We also surveyed the existing theories and methods correspond to infinite variance models in the same chapter. We present a linear filtering method for computing the filter weights assigned to the observation for estimating unobserved signal under general noisy environment in third chapter. Here we consider both the signal and the noise as stationary processes with infinite variance innovations. We derived semi infinite, double infinite and asymmetric signal extraction filters based on minimum dispersion criteria. Finite length filters based on Kalman-Levy filters are developed and identified the pattern of the filter weights. Simulation studies show that the proposed methods are competent enough in signal extraction for processes with infinite variance.Parameter estimation of autoregressive signals observed in a symmetric stable noise environment is discussed in fourth chapter. Here we used higher order Yule-Walker type estimation using auto-covariation function and exemplify the methods by simulation and application to Sea surface temperature data. We increased the number of Yule-Walker equations and proposed a ordinary least square estimate to the autoregressive parameters. Singularity problem of the auto-covariation matrix is addressed and derived a modified version of the Generalized Yule-Walker method using singular value decomposition.In fifth chapter of the thesis we introduced partial covariation function as a tool for stable time series analysis where covariance or partial covariance is ill defined. Asymptotic results of the partial auto-covariation is studied and its application in model identification of stable auto-regressive models are discussed. We generalize the Durbin-Levinson algorithm to include infinite variance models in terms of partial auto-covariation function and introduce a new information criteria for consistent order estimation of stable autoregressive model.In chapter six we explore the application of the techniques discussed in the previous chapter in signal processing. Frequency estimation of sinusoidal signal observed in symmetric stable noisy environment is discussed in this context. Here we introduced a parametric spectrum analysis and frequency estimate using power transfer function. Estimate of the power transfer function is obtained using the modified generalized Yule-Walker approach. Another important problem in statistical signal processing is to identify the number of sinusoidal components in an observed signal. We used a modified version of the proposed information criteria for this purpose.

Statistical signal extraction using stable processes

The standard models for statistical signal extraction assume that the signal and noise are generated by linear Gaussian processes. The optimum filter weights for those models are derived using the method of minimum mean square error. In the present work we study the properties of signal extraction models under the assumption that signal/noise are generated by symmetric stable processes. The optimum filter is obtained by the method of minimum dispersion. The performance of the new filter is compared with their Gaussian counterparts by simulation.

Effects of magnesium stearate on the efficient dispersion of salbutamol sulphate from carrier-based dry powder inhaler formulations

Dry powder inhaler (DPI) formulations is one of the most useful aerosol preparations in which drugs may be formulated as carrier-based interactive mixtures with micronised drug particles (<5 μm) adhered onto the surface of large inert carriers (lactose powders). The addition of magnesium stearate (MgSt) (1-3), was found to increase dispersion of various drugs from DPI formulations. Recently, some active compounds coated with 5% (wt/wt) MgSt using the mechanofusion method showed significant improvements in aerosolization behavior due to the reduction in intrinsic cohesion force (4). Application of MgSt in powder formulations is not new; however, no studies demonstrated the minimum threshold level for this excipient in efficient aerosolization of drug powders from the interactive mixtures. Therefore, this study investigated the role of MgSt concentration on the efficient dispersion of salbutamol sulphate (SS) from DPI formulations.

Non-unitary-weight Space-Time Block Codes with Minimum Decoding Complexity

Space-Time Block Codes (STBCs) from Complex Orthogonal Designs (CODs) are single-symbol decodable/symbol-by-symbol decodable (SSD); however, SSD codes are obtainable from designs that are not CODs. Recently, two such classes of SSD codes have been studied: (i) Coordinate Interleaved Orthogonal Designs (CIODs) and (ii) Minimum-Decoding-Complexity (MDC) STBCs from Quasi-ODs (QODs). The class of CIODs have non-unitary weight matrices when written as a Linear Dispersion Code (LDC) proposed by Hassibi and Hochwald, whereas the other class of SSD codes including CODs have unitary weight matrices. In this paper, we construct a large class of SSD codes with nonunitary weight matrices. Also, we show that the class of CIODs is a special class of our construction.

Fractional quantum Hall edge: Effect of nonlinear dispersion and edge roton

According to Wen's theory, a universal behavior of the fractional quantum Hall edge is expected at sufficiently low energies, where the dispersion of the elementary edge excitation is linear. A microscopic calculation shows that the actual dispersion is indeed linear at low energies, but deviates from linearity beyond certain energy, and also exhibits an "edge roton minimum." We determine the edge exponent from a microscopic approach, and find that the nonlinearity of the dispersion makes a surprisingly small correction to the edge exponent even at energies higher than the roton energy. We explain this insensitivity as arising from the fact that the energy at maximum spectral weight continues to show an almost linear behavior up to fairly high energies. We also study, in an effective-field theory, how interactions modify the exponent for a reconstructed edge with multiple edge modes. Relevance to experiment is discussed.

Damage-tolerant design optimization of laminated composite structures using dispersion of ply angles by genetic algorithm

This article aims to obtain damage-tolerant designs with minimum weight for a laminated composite structure using genetic algorithm. Damage tolerance due to impacts in a laminated composite structure is enhanced by dispersing the plies such that too many adjacent plies do not have the same angle. Weight of the structure is minimized and the Tsai-Wu failure criterion is considered for the safe design. Design variables considered are the number of plies and ply orientation. The influence of dispersed ply angles on the weight of the structure for a given loading conditions is studied by varying the angles in the range of 0 degrees-45 degrees, 0 degrees-60 degrees and 0 degrees-90 degrees at intervals of 5 degrees and by using specific ply angles tailored to loading conditions. A comparison study is carried out between the conventional stacking sequence and the stacking sequence with dispersed ply angles for damage-tolerant weight minimization and some useful designs are obtained. Unconventional stacking sequence is more damage tolerant than the conventional stacking sequence is demonstrated by performing a finite element analysis under both tensile as well as compressive loading conditions. Moreover, a new mathematical function called the dispersion function is proposed to measure the dispersion of ply angles in a laminate. The approach for dispersing ply angles to achieve damage tolerance is especially suited for composite material design space which has multiple local minima.

Design of delay-tolerant linear dispersion codes

In cooperative communication networks, owing to the nodes' arbitrary geographical locations and individual oscillators, the system is fundamentally asynchronous. This will damage some of the key properties of the space-time codes and can lead to substantial performance degradation. In this paper, we study the design of linear dispersion codes (LDCs) for such asynchronous cooperative communication networks. Firstly, the concept of conventional LDCs is extended to the delay-tolerant version and new design criteria are discussed. Then we propose a new design method to yield delay-tolerant LDCs that reach the optimal Jensen's upper bound on ergodic capacity as well as minimum average pairwise error probability. The proposed design employs stochastic gradient algorithm to approach a local optimum. Moreover, it is improved by using simulated annealing type optimization to increase the likelihood of the global optimum. The proposed method allows for flexible number of nodes, receive antennas, modulated symbols and flexible length of codewords. Simulation results confirm the performance of the newly-proposed delay-tolerant LDCs.

An analysis of the accuracy of magnetopause reconnection rate variations deduced from cusp ion dispersion characteristics

We present an analysis of the accuracy of the method introduced by Lockwood et al. (1994) for the determination of the magnetopause reconnection rate from the dispersion of precipitating ions in the ionospheric cusp region. Tests are made by applying the method to synthesised data. The simulated cusp ion precipitation data are produced by an analytic model of the evolution of newly-opened field lines, along which magnetosheath ions are firstly injected across the magnetopause and then dispersed as they propagate into the ionosphere. The rate at which these newly opened field lines are generated by reconnection can be varied. The derived reconnection rate estimates are then compared with the input variation to the model and the accuracy of the method assessed. Results are presented for steady-state reconnection, for continuous reconnection showing a sine-wave variation in rate and for reconnection which only occurs in square wave pulses. It is found that the method always yields the total flux reconnected (per unit length of the open-closed field-line boundary) to within an accuracy of better than 5%, but that pulses tend to be smoothed so that the peak reconnection rate within the pulse is underestimated and the pulse length is overestimated. This smoothing is reduced if the separation between energy channels of the instrument is reduced; however this also acts to increase the experimental uncertainty in the estimates, an effect which can be countered by improving the time resolution of the observations. The limited time resolution of the data is shown to set a minimum reconnection rate below which the method gives spurious short-period oscillations about the true value. Various examples of reconnection rate variations derived from cusp observations are discussed in the light of this analysis.

Paleoamerican Morphology in the Context of European and East Asian Late Pleistocene Variation: Implications for Human Dispersion Into the New World

Early American crania show a different morphological pattern from the one shared by late Native Americans. Although the origin of the diachronic morphological diversity seen on the continents is still debated, the distinct morphology of early Americans is well documented and widely dispersed. This morphology has been described extensively for South America, where larger samples are available. Here we test the hypotheses that the morphology of Early Americans results from retention of the morphological pattern of Late Pleistocene modern humans and that the occupation of the New World precedes the morphological differentiation that gave rise to recent Eurasian and American morphology. We compare Early American samples with European Upper Paleolithic skulls, the East Asian Zhoukoudian Upper Cave specimens and a series of 20 modern human reference crania. Canonical Analysis and Minimum Spanning Tree were used to assess the morphological affinities among the series, while Mantel and Dow-Cheverud tests based on Mahalanobis Squared Distances were used to test different evolutionary scenarios. Our results show strong morphological affinities among the early series irrespective of geographical origin, which together with the matrix analyses results favor the scenario of a late morphological differentiation of modern humans. We conclude that the geographic differentiation of modern human morphology is a late phenomenon that occurred after the initial settlement of the Americas. Am J Phys Anthropol 144:442-453, 2011. (c) 2010 Wiley-Liss, Inc.

Dispersion statistics and a sampling plan for Helicoverpa (Lepidoptera : Noctuidae) on fresh-market tomatoes (Lycopersicon esculentum)

Helicoverpa spp. is the primary pest in the Australian fresh-market tomato industry. We describe the spatial distribution of Helicoverpa spp. eggs on fresh-market tomato crops in the Goulburn Valley region of Victoria, and present a sequential sampling plan for monitoring population densities. The distribution of Helicoverpa spp. eggs was highly contagious, as indicated by a Taylor's b-value of 1.59. This high level of contagion meant that relatively large sample sizes would need to be collected to obtain an estimate of population density. High-precision sampling plans generally necessitated impractical sample sizes, and thus the plan we present is a relatively low-precision level plan (SE/mean = 0.3). Nonetheless, this level of precision is considered adequate for most agronomic scenarios. The plan was validated using a statistical re-sampling approach. The level of precision achieved was generally close to the nominal level. Likewise, the number of samples collected generally showed little departure from the theoretically calculated minimum sample size.

Performance of a reciprocal shaker in mechanical dispersion of soil samples for particle-size analysis

A dispersão da amostra de solo é uma etapa fundamental da análise granulométrica, sendo realizada mediante o uso de dispersantes químicos e agitação mecânica. O objetivo deste trabalho foi avaliar a eficiência de mesa agitadora reciprocante de baixa rotação na dispersão mecânica de amostras de solos de diferentes classes texturais. Foram realizadas análises granulométricas em 61 amostras com quatro repetições, empregando o método da pipeta para determinação da fração argila e tamisagem para determinação das frações areia grossa, areia fina e areia total, sendo o silte determinado por diferença. Na avaliação de desempenho, os resultados obtidos com uso da mesa agitadora reciprocante (MAR) foram comparados com dados disponíveis para as mesmas amostras oriundos de relatórios do Ensaio de Proficiência IAC para Laboratórios de Análises de Solos - Prolab/IAC. Análises de acurácia foram realizadas com base nos valores dos intervalos de confiança definidos para cada fração granulométrica componente de cada amostra ensaiada. Indicadores gráficos também foram utilizados na comparação de dados, por meio de dispersão e ajuste linear. A estatística descritiva indicou preponderância de baixa variabilidade em mais de 90 % dos resultados obtidos para as amostras de texturas arenosa, média e argilosa e em 68 % dos obtidos para as amostras de textura muito argilosa, indicando boa repetibilidade dos resultados obtidos com a MAR. Média variabilidade foi mais frequentemente associada à fração silte, seguida da fração areia fina. Os resultados das análises de sensibilidade indicam acurácia de 100 % nas três frações granulométricas - areia total, silte e argila - para todas as amostras analisadas pertencentes às classes texturais muito argilosa, argilosa e média. Para as nove amostras de textura arenosa, a acurácia média foi de 85,2 %, e os maiores desvios ocorreram em relação à fração silte. Nas aproximações lineares, coeficientes de correlação igual (silte) ou superiores (areia total e argila) a 0,93, bem como diferenças menores do que 0,16 entre os coeficientes angulares das retas e o valor unitário, indicam alta correlação entre os resultados de referência (Prolab/IAC) e os obtidos nos ensaios com a MAR. Conclui-se pelo desempenho satisfatório da mesa agitadora reciprocante de baixa rotação para dispersão mecânica de amostras de solo de diferentes classes texturais para fins de análise granulométrica, permitindo recomendar o uso alternativo do equipamento quando se emprega agitação lenta. As vantagens do uso do equipamento nacional incluem o baixo custo, a possibilidade de análise simultânea de grande número de amostras e o uso de frascos comuns, de vidro ou de plástico, baratos e de fácil reposição.

Minimum Evaporation Model of Dermatological Delivery Systems. Lamellar Liquid Crystal Formulations Containing Brazilian Nut (Bertholletia excelsa HBK) Vegetable Oil and Guarana Glycolic Extract

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Quantum entanglement of bound particles under free center of mass dispersion

On the basis of the full analytical solution of the overall unitary dynamics, the time evolution of entanglement is studied in a simple bipartite model system evolving unitarily from a pure initial state. The system consists of two particles in one spatial dimension bound by harmonic forces and having its free center of mass initially localized in space in a minimum uncertainty wavepacket. The existence of such initial states in which the bound particles are not entangled is discussed. Galilean invariance of the system ensures that the dynamics of entanglement between the two particles is independent of the wavepacket mean momentum. In fact, as shown, it is driven by the dispersive center of mass free dynamics, and evolves in a time scale that depends on the interparticle interaction in an essential way.

Dispersion approach to real and virtual Compton scattering

In recent years, new precision experiments have become possible withthe high luminosity accelerator facilities at MAMIand JLab, supplyingphysicists with precision data sets for different hadronic reactions inthe intermediate energy region, such as pion photo- andelectroproduction and real and virtual Compton scattering.By means of the low energy theorem (LET), the global properties of thenucleon (its mass, charge, and magnetic moment) can be separated fromthe effects of the internal structure of the nucleon, which areeffectively described by polarizabilities. Thepolarizabilities quantify the deformation of the charge andmagnetization densities inside the nucleon in an applied quasistaticelectromagnetic field. The present work is dedicated to develop atool for theextraction of the polarizabilities from these precise Compton data withminimum model dependence, making use of the detailed knowledge of pionphotoproduction by means of dispersion relations (DR). Due to thepresence of t-channel poles, the dispersion integrals for two ofthe six Compton amplitudes diverge. Therefore, we have suggested to subtract the s-channel dispersion integrals at zero photon energy($nu=0$). The subtraction functions at $nu=0$ are calculated through DRin the momentum transfer t at fixed $nu=0$, subtracted at t=0. For this calculation, we use the information about the t-channel process, $gammagammatopipito Nbar{N}$. In this way, four of thepolarizabilities can be predicted using the unsubtracted DR in the $s$-channel. The other two, $alpha-beta$ and $gamma_pi$, are free parameters in ourformalism and can be obtained from a fit to the Compton data.We present the results for unpolarized and polarized RCS observables,%in the kinematics of the most recent experiments, and indicate anenhanced sensitivity to the nucleon polarizabilities in theenergy range between pion production threshold and the $Delta(1232)$-resonance.newlineindentFurthermore,we extend the DR formalism to virtual Compton scattering (radiativeelectron scattering off the nucleon), in which the concept of thepolarizabilities is generalized to the case of avirtual initial photon by introducing six generalizedpolarizabilities (GPs). Our formalism provides predictions for the fourspin GPs, while the two scalar GPs $alpha(Q^2)$ and $beta(Q^2)$ have to befitted to the experimental data at each value of $Q^2$.We show that at energies betweenpion threshold and the $Delta(1232)$-resonance position, thesensitivity to the GPs can be increased significantly, as compared tolow energies, where the LEX is applicable. Our DR formalism can be used for analysing VCS experiments over a widerange of energy and virtuality $Q^2$, which allows one to extract theGPs from VCS data in different kinematics with a minimum of model dependence.