980 resultados para Signal correlation
Resumo:
We study the electronic structure of Sr2RuO4, a noncuprate layered superconductor (T-c=0.93 K), using electron spectroscopy. X-ray photoemission spectroscopy shows that the single particle occupied density of states (DOS) is in fair agreement with the calculated DOS. However, resonant photoemission spectroscopy across the Ru 4p-4d threshold establishes the existence of a correlation satellite to the Ru 4d band. The results indicate substantial charge-transfer character at the Fermi level, with on-site correlations U-dd comparable in magnitude to the Ru-O hopping integral, like the cuprates.
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The paper analyses the effect of spatial smoothing on the performance of MUSIC algorithm. In particular, an attempt is made to bring out two effects of the smoothing: (i) reduction of effective correlation between the impinging signals and (ii) reduction of the noise perturbations due to finite data. For the case of a two-source scenario with widely spaced sources, simplified expressions for improvement with smoothing have been obtained which provide more insight into the impact of smoothing. Specifically, a pessimistic estimate of the minimum value of source correlation beyond which the smoothing is beneficial is brought out by these expressions. Computer simulations are used to demonstrate the usefulness of the analytical results.
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An escape mechanism in a bistable system driven by colored noise of large but finite correlation time (tau) is analyzed. It is shown that the fluctuating potential theory [Phys. Rev. A 38, 3749 (1988)] becomes invalid in a region around the inflection points of the bistable potential, resulting in the underestimation of the mean first passage time at finite tau by this theory. It is shown that transitions at large but finite tau are caused by noise spikes, with edges rising and falling exponentially in a time of O(tau). Simulation of the dynamics of the bistable system driven by noise spikes of the above-mentioned nature clearly reveal the physical mechanism behind the transition.
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Genetic Algorithms are robust search and optimization techniques. A Genetic Algorithm based approach for determining the optimal input distributions for generating random test vectors is proposed in the paper. A cost function based on the COP testability measure for determining the efficacy of the input distributions is discussed, A brief overview of Genetic Algorithms (GAs) and the specific details of our implementation are described. Experimental results based on ISCAS-85 benchmark circuits are presented. The performance pf our GA-based approach is compared with previous results. While the GA generates more efficient input distributions than the previous methods which are based on gradient descent search, the overheads of the GA in computing the input distributions are larger. To account for the relatively quick convergence of the gradient descent methods, we analyze the landscape of the COP-based cost function. We prove that the cost function is unimodal in the search space. This feature makes the cost function amenable to optimization by gradient-descent techniques as compared to random search methods such as Genetic Algorithms.
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The precipitation kinetics of the quenched dilute Ti-1.6 at.-%N alloy has been followed by resistivity measurements at 77 K using the four probe method. Resistivity behaviour has been studied for various durations for the alloys aged in the temperature range 273-373 K. The resistivity behaviour has been explained on the basis of the growth and decay of interfacial strain fields associated with the precipitation process. In addition, the resistivity changes have been correlated with transmission electron microscopy observations. (C) 1995 The Institute of Materials.
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We use the BBGKY hierarchy equations to calculate, perturbatively, the lowest order nonlinear correction to the two-point correlation and the pair velocity for Gaussian initial conditions in a critical density matter-dominated cosmological model. We compare our results with the results obtained using the hydrodynamic equations that neglect pressure and find that the two match, indicating that there are no effects of multistreaming at this order of perturbation. We analytically study the effect of small scales on the large scales by calculating the nonlinear correction for a Dirac delta function initial two-point correlation. We find that the induced two-point correlation has a x(-6) behavior at large separations. We have considered a class of initial conditions where the initial power spectrum at small k has the form k(n) with 0 < n less than or equal to 3 and have numerically calculated the nonlinear correction to the two-point correlation, its average over a sphere and the pair velocity over a large dynamical range. We find that at small separations the effect of the nonlinear term is to enhance the clustering, whereas at intermediate scales it can act to either increase or decrease the clustering. At large scales we find a simple formula that gives a very good fit for the nonlinear correction in terms of the initial function. This formula explicitly exhibits the influence of small scales on large scales and because of this coupling the perturbative treatment breaks down at large scales much before one would expect it to if the nonlinearity were local in real space. We physically interpret this formula in terms of a simple diffusion process. We have also investigated the case n = 0, and we find that it differs from the other cases in certain respects. We investigate a recently proposed scaling property of gravitational clustering, and we find that the lowest order nonlinear terms cause deviations from the scaling relations that are strictly valid in the linear regime. The approximate validity of these relations in the nonlinear regime in l(T)-body simulations cannot be understood at this order of evolution.
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We present the details of a formalism for calculating spatially varying zero-frequency response functions and equal-time correlation functions in models of magnetic and mixed-valence impurities of metals. The method is based on a combination of perturbative, thermodynamic scaling theory [H. R. Krishna-murthy and C. Jayaprakash, Phys. Rev. B 30, 2806 (1984)] and a nonperturbative technique such as the Wilson renormalization group. We illustrate the formalism for the spin-1/2 Kondo problem and present results for the conduction-spin-density�impurity-spin correlation function and conduction-electron charge density near the impurity. We also discuss qualitative features that emerge from our calculations and discuss how they can be carried over to the case of realistic models for transition-metal impurities.
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Effects of basis set and electron correlation on the equilibrium geometry, force constants and vibrational spectra of BH3NH3 have been studied. A series of basis sets ranging from double zeta to triple zeta including polarization and diffuse functions have been utilized. All the SCF based calculations overestimate the dative B-N bond distance and considerable improvement occurs when the treatment for electron correlation is introduced. Detailed vibrational analysis for BH3NH3 has been carried out. The mean absolute percentage deviation of the ab initio predicted vibration frequencies of (BH3NH3)-B-11 from the experiment is about 10% for the SCF based calculations and the MP2 method shows better agreement, the overall deviation being 5-6%. The ground state effective force constants of BH3NH3 were obtained using RECOVES procedure. The RECOVES sets of force constants are found to be highly satisfactory for the prediction of the vibrational frequencies of different isotopomers of BH3NH3. The mean absolute percentage deviation of the calculated frequencies of different isotopomers from the experiment is much less than 1%. The RECOVES-MP2/augDZP set of force constants was found to be the best set among the different sets for this molecule. Theoretical infrared intensities are in fair agreement with the observed spectral features.
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We report the C-HETSERF experiment for determination of long- and short-range homo- and heteronuclear scalar couplings ((n)J(HH) and (n)J(XH), n >= 1) of organic molecules with a low sensitivity dilute heteronucleus in natural abundance. The method finds significant advantage in measurement of relative signs of long-range heteronuclear total couplings in chiral organic liquid crystal. The advantage of the method is demonstrated for the measurement of residual dipolar couplings (RDCs) in enantiomers oriented in the chiral liquid crystal with a focus to unambiguously assign R/S designation in a 2D spectrum. The alignment tensor calculated from the experimental RDCs and with the computed structures of enantiomers obtained by DFT calculations provides the size of the back-calculated RDCs. Smaller root-mean-square deviations (rmsd) between experimental and calculated RDCs indicate better agreement with the input structure and its correct designation of the stereogenic center.
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We propose, for the first time, a reinforcement learning (RL) algorithm with function approximation for traffic signal control. Our algorithm incorporates state-action features and is easily implementable in high-dimensional settings. Prior work, e. g., the work of Abdulhai et al., on the application of RL to traffic signal control requires full-state representations and cannot be implemented, even in moderate-sized road networks, because the computational complexity exponentially grows in the numbers of lanes and junctions. We tackle this problem of the curse of dimensionality by effectively using feature-based state representations that use a broad characterization of the level of congestion as low, medium, or high. One advantage of our algorithm is that, unlike prior work based on RL, it does not require precise information on queue lengths and elapsed times at each lane but instead works with the aforementioned described features. The number of features that our algorithm requires is linear to the number of signaled lanes, thereby leading to several orders of magnitude reduction in the computational complexity. We perform implementations of our algorithm on various settings and show performance comparisons with other algorithms in the literature, including the works of Abdulhai et al. and Cools et al., as well as the fixed-timing and the longest queue algorithms. For comparison, we also develop an RL algorithm that uses full-state representation and incorporates prioritization of traffic, unlike the work of Abdulhai et al. We observe that our algorithm outperforms all the other algorithms on all the road network settings that we consider.
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The interest in low bit rate video coding has increased considerably. Despite rapid progress in storage density and digital communication system performance, demand for data-transmission bandwidth and storage capacity continue to exceed the capabilities of available technologies. The growth of data-intensive digital audio, video applications and the increased use of bandwidth-limited media such as video conferencing and full motion video have not only sustained the need for efficient ways to encode analog signals, but made signal compression central to digital communication and data-storage technology. In this paper we explore techniques for compression of image sequences in a manner that optimizes the results for the human receiver. We propose a new motion estimator using two novel block match algorithms which are based on human perception. Simulations with image sequences have shown an improved bit rate while maintaining ''image quality'' when compared to conventional motion estimation techniques using the MAD block match criteria.
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Asymmetrically dibridged dicopper(II) complexes, [Cu-2(OH)(O2CC6H4-p-Me)(tmen)(2)(H2O)](ClO4)(2) (1) and [Cu-2(OH)(O2CC6H4-p-OMe)(tmen)(2)(H2O)](ClO4)(2) (2) (tmen = N,N,N',N'-tetramethylethane-1,2-diamine), were prepared and structurally characterized. Complex 1 crystallizes in the monoclinic space group P2(1)/a with a = 17.718(2), b = 9.869(1), c = 19.677(2) Angstrom, beta = 115.16(1)degrees, V = 3114.3(6) Angstrom(3) and Z = 4. The structure was refined to R(wR(2)) = 0.067(0.178). Complex 2 crystallizes in the monoclinic space group P2(1)/a with a = 17.695(3), b = 9.574(4), c = 20.104(2) Angstrom, beta = 114.18(1)degrees, V = 3107(1) Angstrom(3) and Z = 4. The final residuals are R(wR(2)) = 0.067(0.182). The complexes have a [Cu-2(mu-OH)(mu-OH)(mu-O2CAr)](2+) core with tmen Ligands occupying the terminal sites of the core. In addition, one copper is axially bound to a water molecule. The Cu ... Cu distances and the Cu-OH Cu angles in the core are 3.394(1) Angstrom, 124.4(2)degrees for 1 and 3.374(1) Angstrom, 123.3(3)degrees for 2. The complexes show axial X-band EPR spectral features in methanol glass at 77 K giving g(perpendicular to) = 2.02, g(parallel to) = 2.3 (A(parallel to) = 165 x 10(-4) cm(-1)) and a visible band near similar to 630 nm in methanol. The complexes are weakly antiferromagnetic. A theoretical fit of the magnetic susceptibility data in the temperature range 40-295 K gives -J = 10 cm(-1), g = 2.05 for 1 and -J = 10 cm(-1), g = 2.0 for 2. Plots of -2J versus the Cu-OH-Cu angle (phi) in this class of asymmetrically dibridged dicopper(II) complexes having d(x2-y2)-d(x2-y2) magnetic orbitals show a linear magneto-structural correlation: -2J(cm(-1)) = 11.48 phi(deg) - 1373.
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The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space view-point is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces f(s) and f(g) and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating f(s) and f(g) is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication-complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. Extensions to the multi-party case is straightforward and is briefly discussed. The average case CC of the relevant greaterthan (CT) function is characterized within two bits. Under the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm. 2010 Elsevier B.V. All rights reserved.
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The statistical performance analysis of ESPRIT, root-MUSIC, minimum-norm methods for direction estimation, due to finite data perturbations, using the modified spatially smoothed covariance matrix, is developed. Expressions for the mean-squared error in the direction estimates are derived based on a common framework. Based on the analysis, the use of the modified smoothed covariance matrix improves the performance of the methods when the sources are fully correlated. Also, the performance is better even when the number of subarrays is large unlike in the case of the conventionally smoothed covariance matrix. However, the performance for uncorrelated sources deteriorates due to an artificial correlation introduced by the modified smoothing. The theoretical expressions are validated using extensive simulations. (C) 1999 Elsevier Science B.V. All rights reserved.