126 resultados para correlation interferometer


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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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We describe direct measurement of phase of ballistic photons transmitted through objects hidden in a turbid medium using a polarization interferometer employing a rotating analyzer. The unwrapped phase difference measurements from interferometry was possible for medium levels of turbidity and accurate phase measurement from the sinusoidal intensity was not detectable when l/l* is increased beyond 4.3. The measured phase on reconstruction using standard tomographic algorithms resulted in the recovery of the refractive index profile of the object hidden in the turbid medium.

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Two families of low correlation QAM sequences are presented here. In a CDMA setting, these sequences have the ability to transport a large amount of data as well as enable variable-rate signaling on the reverse link. The first family Á2SQ - B2− is constructed by interleaving 2 selected QAM sequences. This family is defined over M 2-QAM, where M = 2 m , m ≥ 2. Over 16-QAM, the normalized maximum correlation [`(q)]maxmax is bounded above by <~1.17 ÖNUnknown control sequence '\lesssim' , where N is the period of the sequences in the family. This upper bound on [`(q)]maxmax is the lowest among all known sequence families over 16-QAM.The second family Á4SQ4 is constructed by interleaving 4 selected QAM sequences. This family is defined over M 2-QAM, where M = 2 m , m ≥ 3, i.e., 64-QAM and beyond. The [`(q)]maxmax for sequences in this family over 64-QAM is upper bounded by <~1.60 ÖNUnknown control sequence '\lesssim' . For large M, [`(q)]max <~1.64 ÖNUnknown control sequence '\lesssim' . These upper bounds on [`(q)]maxmax are the lowest among all known sequence families over M 2-QAM, M = 2 m , m ≥ 3.

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A low correlation interleaved QAM sequence family is presented here. In a CDMA setting, these sequences have the ability to transport a large amount of data as well as enable variable-rate signaling on the reverse link. The new interleaved selected family INQ has period N, normalized maximum correlation parameter thetasmacrmax bounded above by lsim a radicN, where a ranges from 1.17 in the 16-QAM case to 1.99 for large M2-QAM, where M = 2m, m ges 2. Each user is enabled to transfer m + 1 bits of data per period of the spreading sequence. These constructions have the lowest known value of maximum correlation of any sequence family with the same alphabet.

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Digital Image Correlation and Tracking (DIC/DDIT) is an optical method that employs tracking & image registration techniques for accurate 2D and 3D measurements of changes in images. This is often used to measure deformation (engineering), displacement, and strain, but it is widely applied in many areas of science and engineering. One very common application is for measuring the motion of an optical mouse.

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This letter proposes a simple tuning algorithm for digital deadbeat control based on error correlation. By injecting a square-wave reference input and calculating the correlation of the control error, a gain correction for deadbeat control is obtained. The proposed solution is simple, it requires a short tuning time, and it is suitable for different DC-DC converter topologies. Simulation and experimental results on synchronous buck converters confirm the properties of the proposed tuning algorithm.

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In this study, we analyse simultaneous measurements (at 50 Hz) of velocity at several heights and shear stress at the surface made during the Utah field campaign for the presence of ranges of scales, where distinct scale-to-scale interactions between velocity and shear stress can be identified. We find that our results are similar to those obtained in a previous study [Venugopal et al., 2003] (contrary to the claim in V2003, that the scaling relations might be dependent on Reynolds number) where wind tunnel measurements of velocity and shear stress were analysed. We use a wavelet-based scale-to-scale cross-correlation to detect three ranges of scales of interaction between velocity and shear stress, namely, (a) inertial subrange, where the correlation is negligible; (b) energy production range, where the correlation follows a logarithmic law; and (c) for scales larger than the boundary layer height, the correlation reaches a plateau.

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We address a certain inverse problem in ultrasound-modulated optical tomography: the recovery of the amplitude of vibration of scatterers [p(r)] in the ultrasound focal volume in a diffusive object from boundary measurement of the modulation depth (M) of the amplitude autocorrelation of light [phi(r, tau)] traversing through it. Since M is dependent on the stiffness of the material, this is the precursor to elasticity imaging. The propagation of phi(r, tau) is described by a diffusion equation from which we have derived a nonlinear perturbation equation connecting p(r) and refractive index modulation [Delta n(r)] in the region of interest to M measured on the boundary. The nonlinear perturbation equation and its approximate linear counterpart are solved for the recovery of p(r). The numerical results reveal regions of different stiffness, proving that the present method recovers p(r) with reasonable quantitative accuracy and spatial resolution. (C) 2011 Optical Society of America