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AuthorTempone, Raul (27)Alouini, Mohamed-Slim (10)Litvinenko, Alexander (9)Bagci, Hakan (8)Ulku, Huseyin Arda (6)View MoreDepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division (49)Applied Mathematics and Computational Science Program (28)Electrical Engineering Program (17)Physical Sciences and Engineering (PSE) Division (5)Mechanical Engineering Program (3)View MoreSubjecthierarchical matrices (3)approximate covariance (1)Chlorophyll-Specific Absorption Coefficient (1)data compression (1)Decomposition (1)View MoreTypePoster (55)Year (Issue Date)

2015 (55)

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Open Access (55)

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Low Complexity Beampattern Design in MIMO Radars Using Planar Array

Bouchoucha, Taha; Ahmed, Sajid; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim (2015-01-07) [Poster]

In multiple-input multiple-output radar systems, it is usually desirable to steer transmitted power in the region-of-interest. To do this, conventional methods optimize the waveform covariance matrix, R, for the desired beampattern, which is then used to generate actual transmitted waveforms. Both steps require constrained optimization, therefore, use iterative and expensive algorithms. In this paper, we provide a closed-form solution to design covariance matrix for the given beampattern using the planar array, which is then used to derive a novel closed-form algorithm to directly design the finite-alphabet constant-envelope (FACE) waveforms. The proposed algorithm exploits the two-dimensional fast-Fourier-transform. The performance of our proposed algorithm is compared with existing methods that are based on semi-definite quadratic programming with the advantage of a considerably reduced complexity.

Computation of Electromagnetic Fields Scattered From Dielectric Objects of Uncertain Shapes Using MLMC

Litvinenko, Alexander; Haji Ali, Abdul Lateef; Uysal, Ismail Enes; Ulku, Huseyin Arda; Tempone, Raul; Bagci, Hakan; Oppelstrup, Jesper (2015-01-07) [Poster]

Simulators capable of computing scattered fields from objects of uncertain shapes are highly useful in electromagnetics and photonics, where device designs are typically subject to fabrication tolerances. Knowledge of statistical variations in scattered fields is useful in ensuring error-free functioning of devices. Oftentimes such simulators use a Monte Carlo (MC) scheme to sample the random domain, where the variables parameterize the uncertainties in the geometry. At each sample, which corresponds to a realization of the geometry, a deterministic electromagnetic solver is executed to compute the scattered fields. However, to obtain accurate statistics of the scattered fields, the number of MC samples has to be large.
This significantly increases the total execution time. In this work, to address this challenge, the Multilevel MC (MLMC [1]) scheme is used together with a (deterministic) surface integral equation solver. The MLMC achieves a higher efficiency by “balancing” the statistical errors due to sampling of the random domain and the numerical errors due to discretization of the geometry at each of these samples. Error balancing results in a smaller number of samples requiring coarser discretizations. Consequently, total execution time is significantly shortened.

Kuramoto model for infinite graphs with kernels

Canale, Eduardo; Tembine, Hamidou; Tempone, Raul; Zouraris, Georgios E. (2015-01-07) [Poster]

In this paper we study the Kuramoto model of weakly coupled oscillators for the case of non trivial network with large number of nodes. We approximate of such configurations by a McKean-Vlasov stochastic differential equation based on infinite graph. We focus on circulant graphs which have enough symmetries to make the computations easier. We then focus on the asymptotic regime where an integro-partial differential equation is derived. Numerical analysis and convergence proofs of the Fokker-Planck-Kolmogorov equation are conducted. Finally, we provide numerical examples that illustrate the convergence of our method.

On the detectability of transverse cracks in laminated composites through measurements of electrical potential change

Selvakumaran, Lakshmi; Long, Quan; Prudhomme, Serge; Lubineau, Gilles (2015-01-07) [Poster]

For structures made of laminated composites, real-time structural health monitoring is necessary as significant damage may occur without any visible signs on the surface. Inspection by electrical tomography seems a viable approach as the technique relies on voltage measurements from a network of electrodes over the boundary of the inspected domain to infer the change in conductivity within the bulk material. The change in conductivity, if significant, can be correlated to the degradation state of the material, allowing damage detection. We focus here on the detection of the transverse cracking mechanism which modifies the in-plane transverse conductivity of ply. The quality of detection is directly related to the sensitivity of the voltage measurements with respect to the presence of cracks. We demonstrate here from numerical experiments that the sensitivity depends on several parameters, such as the anisotropy in the electrical conductivity of the baseline composite ply or the geometricalparameters of the structure. Based on these results, applicability of electrical tomography to detect transverse cracks in a laminate is discussed.

An A Posteriori Error Estimate for Symplectic Euler Approximation of Optimal Control Problems

Karlsson, Peer Jesper; Larsson, Stig; Sandberg, Mattias; Szepessy, Anders; Tempone, Raul (2015-01-07) [Poster]

This work focuses on numerical solutions of optimal control problems. A time discretization error representation is derived for the approximation of the associated value function. It concerns Symplectic Euler solutions of the Hamiltonian system connected with the optimal control problem. The error representation has a leading order term consisting of an error density that is computable from Symplectic Euler solutions. Under an assumption of the pathwise convergence of the approximate dual function as the maximum time step goes to zero, we prove that the remainder is of higher order than the leading error density part in the error representation. With the error representation, it is possible to perform adaptive time stepping. We apply an adaptive algorithm originally developed for ordinary differential equations.

Optimal Experimental Design of Furan Shock Tube Kinetic Experiments

Kim, Daesang; Long, Quan; Bisetti, Fabrizio; Farooq, Aamir; Tempone, Raul; Knio, Omar (2015-01-07) [Poster]

A Bayesian optimal experimental design methodology has been developed and applied to refine the rate coefficients of elementary reactions in Furan combustion. Furans are considered as potential renewable fuels. We focus on the Arrhenius rates of Furan + OH ↔ Furyl-2 + H2O and Furan ↔ OH Furyl-3 + H2O, and rely on the OH consumption rate as experimental observable. A polynomial chaos surrogate is first constructed using an adaptive pseudo-spectral projection algorithm. The PC surrogate is then exploited in conjunction with a fast estimation of the expected information gain in order to determine the optimal design in the space of initial temperatures and OH concentrations.

Analysis of Transient Electromagnetic Wave Interactions on Graphene Sheets Using Integral Equations

Shi, Yifei; Sandhu, Ali Imran; Li, Peng; Uysal, Ismail Enes; Ulku, Huseyin Arda; Bagci, Hakan (2015-01-07) [Poster]

Spectral Uncertainty Analysis of Ionic Reactions in Methane Combustion

Kim, Daesang; Han, Jie; Bisetti, Fabrizio; Farooq, Aamir; Knio, Omar (2015-01-07) [Poster]

Multiscale Modeling of Wear Degradation

Moraes, Alvaro; Ruggeri, Fabrizio; Tempone, Raul; Vilanova, Pedro (2015-01-07) [Poster]

Cylinder liners of diesel engines used for marine propulsion are naturally subjected to a wear process, and may fail when their wear exceeds a specified limit. Since failures often represent high economical costs, it is utterly important to predict and avoid them. In this work [4], we model the wear process using a pure jump process. Therefore, the inference goal here is to estimate: the number of possible jumps, its sizes, the coefficients and the shapes of the jump intensities. We propose a multiscale approach for the inference problem that can be seen as an indirect inference scheme. We found that using a Gaussian approximation based on moment expansions, it is possible to accurately estimate the jump intensities and the jump amplitudes. We obtained results equivalent to the state of the art but using a simpler and less expensive approach.

Secret-Sharing over Multiple-Antenna Channels with Transmit Correlation

Zorgui, Marwen; Rezki, Zouheir; Alomair, Basel; Alouini, Mohamed-Slim (2015-01-07) [Poster]

We consider secret-key agreement with public discussion over Rayleigh fastfading channels with transmit correlation. The legitimate receiver and the eavesdropper are assumed to have perfect channel knowledge while the transmitter has only knowledge of the transmit correlation matrix. First, We derive the expression of the key capacity under the considered setup. Then, we show that the optimal transmit strategy achieving the key capacity consists in transmitting Gaussian signals along the eingenvectors of the channel covariance matrix. The powers allocated to each channel mode are determined as the solution of a numerical optimization problem that we derive. We also provide a waterfilling interpretation of the optimal power allocation. Finally, we develop a necessary and sufficient condition for beamforming to be optimal, i.e., transmitting along the strongest channel mode only is key capacity-achieving.

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