991 resultados para Fitzgerald, Dennis
Resumo:
In this paper, an introduction to Bayesian methods in signal processing will be given. The paper starts by considering the important issues of model selection and parameter estimation and derives analytic expressions for the model probabilities of two simple models. The idea of marginal estimation of certain model parameter is then introduced and expressions are derived for the marginal probability densities for frequencies in white Gaussian noise and a Bayesian approach to general changepoint analysis is given. Numerical integration methods are introduced based on Markov chain Monte Carlo techniques and the Gibbs sampler in particular.
Resumo:
In multi-carrier systems, small carrier frequency offsets result in significant degradation of performance and this offset should be compensated before demodulation can be performed. In this paper, we consider a generic multi-carrier system with pulse shaping and estimate the frequency offset by exploiting the cyclostationarity of the received signal. By transforming the time domain signal to the cyclic correlation domain we are able to estimate the frequency offset without the aid of pilot symbols or the cyclic prefix. The Bayesian framework is used to obtain the estimate and we show how we can simplify the estimation process. © 1999 IEEE.
Resumo:
In this paper, an introduction to Bayesian methods in signal processing will be given. The paper starts by considering the important issues of model selection and parameter estimation and derives analytic expressions for the model probabilities of two simple models. The idea of marginal estimation of certain model parameter is then introduced and expressions are derived for the marginal probabilitiy densities for frequencies in white Gaussian noise and a Bayesian approach to general changepoint analysis is given. Numerical integration methods are introduced based on Markov chain Monte Carlo techniques and the Gibbs sampler in particular.
Resumo:
The application of Bayes' Theorem to signal processing provides a consistent framework for proceeding from prior knowledge to a posterior inference conditioned on both the prior knowledge and the observed signal data. The first part of the lecture will illustrate how the Bayesian methodology can be applied to a variety of signal processing problems. The second part of the lecture will introduce the concept of Markov Chain Monte-Carlo (MCMC) methods which is an effective approach to overcoming many of the analytical and computational problems inherent in statistical inference. Such techniques are at the centre of the rapidly developing area of Bayesian signal processing which, with the continual increase in available computational power, is likely to provide the underlying framework for most signal processing applications.
Resumo:
Models for simulating Scanning Probe Microscopy (SPM) may serve as a reference point for validating experimental data and practice. Generally, simulations use a microscopic model of the sample-probe interaction based on a first-principles approach, or a geometric model of macroscopic distortions due to the probe geometry. Examples of the latter include use of neural networks, the Legendre Transform, and dilation/erosion transforms from mathematical morphology. Dilation and the Legendre Transform fall within a general family of functional transforms, which distort a function by imposing a convex solution.In earlier work, the authors proposed a generalized approach to modeling SPM using a hidden Markov model, wherein both the sample-probe interaction and probe geometry may be taken into account. We present a discussion of the hidden Markov model and its relationship to these convex functional transforms for simulating and restoring SPM images.©2009 SPIE.
Resumo:
We propose a system that can reliably track multiple cars in congested traffic environments. Our system's key basis is the implementation of a sequential Monte Carlo algorithm, which introduces robustness against problems arising due to the proximity between vehicles. By directly modelling occlusions and collisions between cars we obtain promising results on an urban traffic dataset. Extensions to this initial framework are also suggested. © 2010 IEEE.
Resumo:
The seeded infiltration and growth (SIG) technique offers near-net shape processing of bulk superconductors with significant improvement in reduced Y2BaCuO5 (Y-211) inclusion size, reduced shrinkage, reduced porosity and improved current density compared to samples fabricated by top seeded melt growth (TSMG). Y2Ba4CuMOy phases where M=Nb, Mo, W, Ta, etc., have been shown to form nano-scale inclusions in the YBa2Cu3Oy (Y-123) phase matrix and to contribute to enhanced magnetic flux pinning in these materials. In this paper, we describe the introduction of Y2Ba 4CuWOy nano-scale inclusions into bulk superconductors processed by the seeded infiltration growth process. Critical current density, Jc, in excess of 105 A/cm2 at 77 K in self-field is observed for samples containing Y2Ba 4CuWOy. © 2011 IEEE.
Resumo:
Y-Ba-Cu-O (YBCO) single grains have the potential to generate large trapped magnetic fields for engineering applications, and research on the processing and properties of this material has attracted interest world-wide over the past 20 years. In particular, the introduction of flux pinning centers to the large grain microstructure to improve its current density Jc, and hence trapped field, has been investigated extensively. Y2Ba 4CuMO2 [Y-2411(M)], where M = Nb, Ta, Mo, W, Ru, Zr, Bi and Ag, has been discovered recently to form very effective flux pinning centers due primarily to its ability to form nano-size inclusions in the superconducting phase matrix. However, the addition of the Y-2411(M) phase to the precursor composition complicates the melt-processing of single grains. The addition of Y2O3 to the precursor composition, however, broadens the growth window of single YBCO grains containing Y-2411 (M). We report an investigation of the microstructures and superconducting properties of single grains of this composition grown by top seeded melt growth (TSMG). © 2010 IEEE.
Resumo:
This study examines the kinetics of carbonation by CO2 at temperatures of ca. 750 °C of a synthetic sorbent composed of 15 wt% mayenite (Ca12Al14O33) and CaO, designated HA-85-850, and draws comparisons with the carbonation of a calcined limestone. In-situ XRD has verified the inertness of mayenite, which neither interacts with the active CaO nor does it significantly alter the CaO carbonation–calcination equilibrium. An overlapping grain model was developed to predict the rate and extent of carbonation of HA-85-850 and limestone. In the model, the initial microstructure of the sorbent was defined by a discretised grain size distribution, assuming spherical grains. The initial input to the model – the size distribution of grains – was a fitted parameter, which was in good agreement with measurements made with mercury porosimetry and by the analysis of SEM images of sectioned particles. It was found that the randomly overlapping spherical grain assumption offered great simplicity to the model, despite its approximation to the actual porous structure within a particle. The model was able to predict the performance of the materials well and, particularly, was able to account for changes in rate and extent of reaction as the structure evolved after various numbers of cycles of calcination and carbonation.
Resumo:
This study examines the kinetics of carbonation by CO 2 at temperatures of ca. 750°C of a synthetic sorbent composed of 15wt% mayenite (Ca 12Al 14O 33) and CaO, designated HA-85-850, and draws comparisons with the carbonation of a calcined limestone. In-situ XRD has verified the inertness of mayenite, which neither interacts with the active CaO nor does it significantly alter the CaO carbonation-calcination equilibrium. An overlapping grain model was developed to predict the rate and extent of carbonation of HA-85-850 and limestone. In the model, the initial microstructure of the sorbent was defined by a discretised grain size distribution, assuming spherical grains. The initial input to the model - the size distribution of grains - was a fitted parameter, which was in good agreement with measurements made with mercury porosimetry and by the analysis of SEM images of sectioned particles. It was found that the randomly overlapping spherical grain assumption offered great simplicity to the model, despite its approximation to the actual porous structure within a particle. The model was able to predict the performance of the materials well and, particularly, was able to account for changes in rate and extent of reaction as the structure evolved after various numbers of cycles of calcination and carbonation. © 2011 Elsevier Ltd.
Resumo:
Single grain REBa2C3uO7 ((RE)BCO, where RE is a rare earth element or yttrium) bulk superconducting materials have significant potential for a variety of engineering applications due to their ability to trap high magnetic fields. However, it is well known that the presence of grain boundaries coupled with a high angle of misorientation (typically 5�) significantly reduces the critical current density, J c , in all forms of high temperature superconducting materials. It is of considerable fundamental and technological interest, therefore, to investigate the grain boundary properties of bulk, film and tape (RE)BCO. We report a successful multi-seeding technique for the fabrication of fully aligned, artificial (0��misalignment) grain boundaries within large grain YBCO bulk superconductors using bridge-shaped seeds. The microstructure and critical current densities of the grain boundaries produced by this technique have been studied in detail.
Resumo:
The attrition of two potential oxygen-carriers for chemical-looping, 100. wt% mechanically-mixed, unsupported iron oxide (400-600 μm diameter) and 25. wt% copper oxide impregnated on alumina (600-900 μm diameter), has been studied. The rates of attrition of batches of these particles whilst they were being fluidised and subjected to successive cycles of reduction and oxidation were determined by measuring the rate of production of fine particles elutriated from the bed, as well as progressive changes in the distribution of particle sizes retained in the bed. The ability of the particles to withstand impacts was also investigated by examining the degree of fragmentation of 1. g of reacted particles of known size on projecting them at a target at various velocities. It was found that the mechanical strength of the iron oxide particles deteriorated significantly after repeated cycles of oxidation and reduction. Thus, the rate of elutriation increased ~35-fold between the 1st and 10th cycle. At an impact velocity of 38. m/s, the amount of fragmentation in the impact test, viz. mass fraction of particles after impact having a size less than that before impact, increased from ~2.3. wt% (fresh particles) to 98. wt% after the 10th cycle. The CuO particles, in comparison, were able to withstand repeated reaction: no signs of increased rates of elutriation or fragmentation were observed over ten cycles. These results highlight the importance of selecting a durable support for oxygen-carriers. © 2011 Elsevier Ltd.
Resumo:
A lattice Boltzmann method is used to model gas-solid reactions where the composition of both the gas and solid phase changes with time, while the boundary between phases remains fixed. The flow of the bulk gas phase is treated using a multiple relaxation time MRT D3Q19 model; the dilute reactant is treated as a passive scalar using a single relaxation time BGK D3Q7 model with distinct inter- and intraparticle diffusivities. A first-order reaction is incorporated by modifying the method of Sullivan et al. [13] to include the conversion of a solid reactant. The detailed computational model is able to capture the multiscale physics encountered in reactor systems. Specifically, the model reproduced steady state analytical solutions for the reaction of a porous catalyst sphere (pore scale) and empirical solutions for mass transfer to the surface of a sphere at Re=10 (particle scale). Excellent quantitative agreement between the model and experiments for the transient reduction of a single, porous sphere of Fe 2O 3 to Fe 3O 4 in CO at 1023K and 10 5Pa is demonstrated. Model solutions for the reduction of a packed bed of Fe 2O 3 (reactor scale) at identical conditions approached those of experiments after 25 s, but required prohibitively long processor times. The presented lattice Boltzmann model resolved successfully mass transport at the pore, particle and reactor scales and highlights the relevance of LB methods for modelling convection, diffusion and reaction physics. © 2012 Elsevier Inc.