994 resultados para Symmetric Function
Resumo:
High-angular resolution diffusion imaging (HARDI) can reconstruct fiber pathways in the brain with extraordinary detail, identifying anatomical features and connections not seen with conventional MRI. HARDI overcomes several limitations of standard diffusion tensor imaging, which fails to model diffusion correctly in regions where fibers cross or mix. As HARDI can accurately resolve sharp signal peaks in angular space where fibers cross, we studied how many gradients are required in practice to compute accurate orientation density functions, to better understand the tradeoff between longer scanning times and more angular precision. We computed orientation density functions analytically from tensor distribution functions (TDFs) which model the HARDI signal at each point as a unit-mass probability density on the 6D manifold of symmetric positive definite tensors. In simulated two-fiber systems with varying Rician noise, we assessed how many diffusionsensitized gradients were sufficient to (1) accurately resolve the diffusion profile, and (2) measure the exponential isotropy (EI), a TDF-derived measure of fiber integrity that exploits the full multidirectional HARDI signal. At lower SNR, the reconstruction accuracy, measured using the Kullback-Leibler divergence, rapidly increased with additional gradients, and EI estimation accuracy plateaued at around 70 gradients.
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Diffusion weighted magnetic resonance imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of six directions, second-order tensors (represented by three-by-three positive definite matrices) can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve more complicated white matter configurations, e.g., crossing fiber tracts. Recently, a number of high-angular resolution schemes with more than six gradient directions have been employed to address this issue. In this article, we introduce the tensor distribution function (TDF), a probability function defined on the space of symmetric positive definite matrices. Using the calculus of variations, we solve the TDF that optimally describes the observed data. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function. Moreover, a tensor orientation distribution function (TOD) may also be derived from the TDF, allowing for the estimation of principal fiber directions and their corresponding eigenvalues.
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In this paper, we first recast the generalized symmetric eigenvalue problem, where the underlying matrix pencil consists of symmetric positive definite matrices, into an unconstrained minimization problem by constructing an appropriate cost function, We then extend it to the case of multiple eigenvectors using an inflation technique, Based on this asymptotic formulation, we derive a quasi-Newton-based adaptive algorithm for estimating the required generalized eigenvectors in the data case. The resulting algorithm is modular and parallel, and it is globally convergent with probability one, We also analyze the effect of inexact inflation on the convergence of this algorithm and that of inexact knowledge of one of the matrices (in the pencil) on the resulting eigenstructure. Simulation results demonstrate that the performance of this algorithm is almost identical to that of the rank-one updating algorithm of Karasalo. Further, the performance of the proposed algorithm has been found to remain stable even over 1 million updates without suffering from any error accumulation problems.
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Convex potential minimisation is the de facto approach to binary classification. However, Long and Servedio [2008] proved that under symmetric label noise (SLN), minimisation of any convex potential over a linear function class can result in classification performance equivalent to random guessing. This ostensibly shows that convex losses are not SLN-robust. In this paper, we propose a convex, classification-calibrated loss and prove that it is SLN-robust. The loss avoids the Long and Servedio [2008] result by virtue of being negatively unbounded. The loss is a modification of the hinge loss, where one does not clamp at zero; hence, we call it the unhinged loss. We show that the optimal unhinged solution is equivalent to that of a strongly regularised SVM, and is the limiting solution for any convex potential; this implies that strong l2 regularisation makes most standard learners SLN-robust. Experiments confirm the unhinged loss’ SLN-robustness.
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The problem of a long, thin circular cylindrical shell enclosed in an elastic casing and subjected to a ring of radial load on the inner rim is solved using the Love function for the casing in conjunction with Flügge shell theory. Numerical work has been done with a digital computer and the results for stress and displacement fields are given for various values of the shell geometry parameters and material constants.
Resumo:
This paper investigates the loss of high mass ions due to their initial thermal energy in ion trap mass analyzers. It provides an analytical expression for estimating the percentage loss of ions of a given mass at a particular temperature, in a trap operating under a predetermined set of conditions. The expression we developed can be used to study the loss of ions due to its initial thermal energy in traps which have nonlinear fields as well as those which have linear fields. The expression for the percentage of ions lost is shown to be a function of the temperature of the ensemble of ions, ion mass and ion escape velocity. An analytical expression for the escape velocity has also been derived in terms of the trapping field, drive frequency and ion mass. Because the trapping field is determined by trap design parameters and operating conditions, it has been possible to study the influence of these parameters on ion loss. The parameters investigated include ion temperature, magnitude of the initial potential applied to the ring electrode (which determines the low mass cut-off), trap size, dimensions of apertures in the endcap electrodes and RF drive frequency. Our studies demonstrate that ion loss due to initial thermal energy increases with increase in mass and that, in the traps investigated, ion escape occurs in the radial direction. Reduction in the loss of high mass ions is favoured by lower ion temperatures, increasing low mass cut-off, increasing trap size, and higher RF drive frequencies. However, dimensions of the apertures in the endcap electrodes do not influence ion loss in the range of aperture sizes considered. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
Surface-potential-based compact charge models for symmetric double-gate metal-oxide-semiconductor field-effect transistors (SDG-MOSFETs) are based on the fundamental assumption of having equal oxide thicknesses for both gates. However, for practical devices, there will always be some amount of asymmetry between the gate oxide thicknesses due to process variations and uncertainties, which can affect device performance significantly. In this paper, we propose a simple surface-potential-based charge model, which is applicable for tied double-gate MOSFETs having same gate work function but could have any difference in gate oxide thickness. The proposed model utilizes the unique so-far-unexplored quasi-linear relationship between the surface potentials along the channel. In this model, the terminal charges could be computed by basic arithmetic operations from the surface potentials and applied biases, and thus, it could be implemented in any circuit simulator very easily and extendable to short-channel devices. We also propose a simple physics-based perturbation technique by which the surface potentials of an asymmetric device could be obtained just by solving the input voltage equation of SDG devices for small asymmetry cases. The proposed model, which shows excellent agreement with numerical and TCAD simulations, is implemented in a professional circuit simulator through the Verilog-A interface and demonstrated for a 101-stage ring oscillator simulation. It is also shown that the proposed model preserves the source/drain symmetry, which is essential for RF circuit design.
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Edge cracked specimens have been widely utilized for fracture testing. Edge cracked semicircular disk (ECSD) specimen has now been well characterized with regard to its form factor and weight function. This paper presents a modified semicircular ring version of this specimen to enhance the form factor in general while retaining other desirable features. The efficacy of the modified design is proved by combining theory of elasticity solutions with finite element results to arrive at the optimum design geometry. New insights emerging from this work are used to theoretically re-examine the arch-tension and the four-point bend specimens. (C) 2014 Elsevier Ltd. All rights reserved.
Resumo:
The K-user multiple input multiple output (MIMO) Gaussian symmetric interference channel where each transmitter has M antennas and each receiver has N antennas is studied from a generalized degrees of freedom (GDOF) perspective. An inner bound on the GDOF is derived using a combination of techniques such as treating interference as noise, zero forcing (ZF) at the receivers, interference alignment (IA), and extending the Han-Kobayashi (HK) scheme to K users, as a function of the number of antennas and the log INR/log SNR level. Several interesting conclusions are drawn from the derived bounds. It is shown that when K > N/M + 1, a combination of the HK and IA schemes performs the best among the schemes considered. When N/M < K <= N/M + 1, the HK-scheme outperforms other schemes and is found to be GDOF optimal in many cases. In addition, when the SNR and INR are at the same level, ZF-receiving and the HK-scheme have the same GDOF performance.
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Finite-fringe interferograms produced for axisymmetric shock wave flows are analyzed by Fourier transform fringe analysis and an Abel inversion method to produce density field data for the validation of numerical models. For the Abel inversion process, we use basis functions to model phase data from axially-symmetric shock wave structure. Steady and unsteady flow problems are studied, and compared with numerical simulations. Good agreement between theoretical and experimental results is obtained when one set of basis functions is used during the inversion process, but the shock front is smeared when another is used. This is because each function in the second set of basis functions is infinitely differentiable, making them poorly-suited to the modelling of a step function as is required in the representation of a shock wave.
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Two sensitive polarized spectroscopies, reflectance difference spectroscopy and photocurrent difference spectroscopy, are used to study the characteristic of the in-plane optical anisotropy in the symmetric and the asymmetric (001) GaAs/Al(Ga)As superlattices (SLs). The anisotropy spectra of the symmetric and the asymmetric SLs show significant difference: for symmetric ones, the anisotropies of the 1HH-->1E transition (1H1E) and 1L1E are dominant, and they are always approximately equal and opposite; while for asymmetric ones, the anisotropy of 1H1E is much less than that of 1L1E and 2H1E, and the anisotropy of 3H2E is very strong. The calculated anisotropy spectra within the envelope function model agree with the experimental results, and a perturbation approach is used to understand the role of the electric field and the interface potential in the anisotropy. (C) 2001 American Institute of Physics.
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General expressions used for transforming raw laser-induced fluorescence (LIF) intensity into the population and alignment parameters of a symmetric top molecule are derived by employing the density matrix approach. The molecular population and alignment are described by molecular state multipoles. The results are presented for a general excitation-detection geometry and then applied to some special geometries. In general cases, the LIF intensity is a complex function of the initial molecular state multipoles, the dynamic factors and the excitation-detection geometrical factors. It contains a population and 14 alignment multipoles. How to extract all initial state multipoles from the rotationally unresolved emission LIF intensity is discussed in detail.
Resumo:
General expressions used for extracting the orientation and alignment parameters of a symmetric top molecule from laser-induced fluorescence (LIF) intensity are derived by employing the density matrix approach. The molecular orientation and alignment are described by molecular state multipoles. Excitation and detection are circularly and linearly polarized lights, respectively. In general cases, the LIF intensity is a complex function of the initial molecular state multipoles, the dynamic factors and the excitation-detection geometrical factors. It contains a population, ten orientation and fourteen alignment multipoles. The problem of how to extract the initial molecular state multipoles from the resolved LIF intensity is discussed.
Resumo:
Expressions used for extracting the population and alignment parameters of a symmetric top molecule from (n + 1) laser-induced fluorescence (LIF) are derived by employing the tensor density matrix method. The molecular population and alignment are described by molecular state multipoles. The LIF intensity is a complex function of the initial molecular state multipoles, the dynamic factors, and the excitation-detection geometrical factors. The problem of how to extract the initial molecular state multipoles from (2 + 1) LIF, as an example, is discussed in detail. (C) 2000 American Institute of Physics. [S0021-9606(00)30744-9].
Resumo:
We consider a knapsack problem to minimize a symmetric quadratic function. We demonstrate that this symmetric quadratic knapsack problem is relevant to two problems of single machine scheduling: the problem of minimizing the weighted sum of the completion times with a single machine non-availability interval under the non-resumable scenario; and the problem of minimizing the total weighted earliness and tardiness with respect to a common small due date. We develop a polynomial-time approximation algorithm that delivers a constant worst-case performance ratio for a special form of the symmetric quadratic knapsack problem. We adapt that algorithm to our scheduling problems and achieve a better performance. For the problems under consideration no fixed-ratio approximation algorithms have been previously known.