Browsing by Subject "Computational efficiency"

Now showing 1 - 11 of 11

Open Access
Analysis of photonic-crystal problems with MLFMA and approximate Schur preconditioners
(IEEE, 2009-07) Ergül, Özgür; Malas, Tahir; Kılınç, Seçil; Sarıtaş, Serkan; Gürel, Levent
We consider fast and accurate solutions of electromagnetics problems involving three-dimensional photonic crystals (PhCs). Problems are formulated with the combined tangential formulation (CTF) and the electric and magnetic current combined-field integral equation (JMCFIE) discretized with the Rao-Wilton-Glisson functions. Matrix equations are solved iteratively by the multilevel fast multipole algorithm. Since PhC problems are difficult to solve iteratively, robust preconditioning techniques are required to accelerate iterative solutions. We show that novel approximate Schur preconditioners enable efficient solutions of PhC problems by reducing the number of iterations significantly for both CTF and JMCFIE. ©2009 IEEE.
Open Access
Analytical evaluation of the MoM matrix elements
(Institute of Electrical and Electronics Engineers, 1996-04) Alatan, L.; Aksun, M. I.; Mahadevan, K.; Birand, M. T.
Derivation of the closed-form Green's functions has eliminated the computationally expensive evaluation of the Sommerfeld integrals to obtain the Green's functions in the spatial domain. Therefore, using the closed-form Green's functions in conjunction with the method of moments (MoM) has unproved the computational efficiency of the technique significantly. Further improvement can be achieved on the calculation of the matrix elements involved in the MoM, usually double integrals for planar geometries, by eliminating the numerical integration. The contribution of this paper is to present the analytical evaluation of the matrix elements when the closed-form Green's functions are used, and to demonstrate the amount of improvement in computation time. © 1996 IEEE.
Open Access
A Benders decomposition approach for the charging station location problem with plug-in hybrid electric vehicles
(Elsevier, 2016) Arslan, O.; Karaşan, O. E.
The flow refueling location problem (FRLP) locates p stations in order to maximize the flow volume that can be accommodated in a road network respecting the range limitations of the vehicles. This paper introduces the charging station location problem with plug-in hybrid electric vehicles (CSLP-PHEV) as a generalization of the FRLP. We consider not only the electric vehicles but also the plug-in hybrid electric vehicles when locating the stations. Furthermore, we accommodate multiple types of these vehicles with different ranges. Our objective is to maximize the vehicle-miles-traveled using electricity and thereby minimize the total cost of transportation under the existing cost structure between electricity and gasoline. This is also indirectly equivalent to maximizing the environmental benefits. We present an arc-cover formulation and a Benders decomposition algorithm as exact solution methodologies to solve the CSLP-PHEV. The decomposition algorithm is accelerated using Pareto-optimal cut generation schemes. The structure of the formulation allows us to construct the subproblem solutions, dual solutions and nondominated Pareto-optimal cuts as closed form expressions without having to solve any linear programs. This increases the efficiency of the decomposition algorithm by orders of magnitude and the results of the computational studies show that the proposed algorithm both accelerates the solution process and effectively handles instances of realistic size for both CSLP-PHEV and FRLP.
Open Access
Computationally efficient wavelet affine invariant functions for shape recognition
(IEEE, 2004) Bala, E.; Çetin, A. Enis
An affine invariant function for object recognition is constructed from wavelet coefficients of the object boundary. In previous works, undecimated dyadic wavelet transform was used to construct affine invariant functions. In this paper, an algorithm based on decimated wavelet transform is developed to compute an affine invariant function. As a result computational complexity is reduced without decreasing recognition performance. Experimental results are presented. © 2004 IEEE.
Open Access
Fast and accurate solutions of extremely large scattering problems involving three-dimensional canonical and complicated objects
(IEEE, 2009-07) Ergül, Özgür; Gürel, Levent
We present fast and accurate solutions of extremely large scattering problems involving three-dimensional metallic objects discretized with hundreds of millions of unknowns. Solutions are performed by the multilevel fast multipole algorithm, which is parallelized efficiently via a hierarchical partition strategy. Various examples involving canonical and complicated objects are presented in order to demonstrate the feasibility of accurately solving large-scale problems on relatively inexpensive computing platforms without resorting to approximation techniques. ©2009 IEEE.
Open Access
Hybridizing physical optics with MLFMA for efficient scattering computations of three-dimensional complex targets
(IEEE, 2009-07) Manyas, Alp; Ergül, Özgür; Gürel, Levent
The multilevel fast multipole algorithm (MLFMA) provides accurate and efficient solutions of electromagnetic scattering problems involving large and complicated structures. On the other hand, whenever applicable, accelerations provided by approximation techniques can be useful to further improve the efficiency of solutions. In this paper, we present a hybrid technique, which combines the physical-optics (PO) method and MLFMA for efficient scattering computations of three-dimensional objects. We show that, with a careful choice of MLFMA and PO regions on the structure, the number of unknowns can be reduced and solutions can be accelerated significantly, without sacrificing the accuracy. The proposed hybrid technique is easy to implement by modifying existing MLFMA codes. ©2009 IEEE.
Open Access
Mixture of set membership filters approach for big data signal processing
(IEEE, 2016) Kılıç, O. Fatih; Sayın, M. Ömer; Delibalta, İ.; Kozat, Süleyman Serdar
In this work, we propose a new approach for mixture of adaptive filters based on set-membership filters (SMF) which is specifically designated for big data signal processing applications. By using this approach, we achieve significantly reduced computational load for the mixture methods with better performance in convergence rate and steady-state error with respect to conventional mixture methods. Finally, we approve these statements with the simulations done on produce data.
Open Access
Online adaptive hierarchical space partitioning classifier
(IEEE, 2016) Kılıç, O. Fatih; Vanlı, N. D.; Özkan, Hüseyin; Delibalta, İ.; Kozat, Süleyman Serdar
We introduce an on-line classification algorithm based on the hierarchical partitioning of the feature space which provides a powerful performance under the defined empirical loss. The algorithm adaptively partitions the feature space and at each region trains a different classifier. As a final classification result algorithm adaptively combines the outputs of these basic models which enables it to create a linear piecewise classifier model that can work well under highly non-linear complex data. The introduced algorithm also have scalable computational complexity that scales linearly with dimension of the feature space, depth of the partitioning and number of processed data. Through experiments we show that the introduced algorithm outperforms the state-of-the-art ensemble techniques over various well-known machine learning data sets.
Open Access
Reconstruction of scalar diffraction field from distributed data points over 3D space
(IEEE, 2007) Esmer, G. Bora; Uzunov, V.; Onural, Levent; Gotchev, A.; Özaktaş, Haldun M.
Diffraction field computation is an important task in the signal conversion stage of the holographic 3DTV. We consider an abstract setting, where the diffraction field of the desired 3D scene to be displayed is given by discrete samples distributed over 3D space. Based on these samples, a model of the diffraction field should be built to allow the field computation at any desired point. In our previous works, we have proved our concepts for the simplistic 2D case. In this paper, we generalize the earlier proposed techniques, namely the projection onto convex sets and conjugate gradient based techniques and test them for their computational efficiency and memory requirements for a specific 3D case.
Open Access
Signal processing for three-dimensional holographic television displays that use binary spatial light modulators
(IEEE, 2010) Ulusoy, Erdem; Onural, Levent; Özaktaş, Haldun M.
One of the important techniques used for three dimensional television (3DTV) is holography. In holographic 3DTV, spatial light modulators (SLM) are used as the display device. SLMs that provide the most limited modulation are the binary SLMs, since only two different values can be assigned to their pixels. An important signal processing problem arising here is the determination of the binary signal to be written on the SLM among the possible ones such that the desired light field is generated to the best extent. Many of the proposed methods do not produce satisfactory results in terms of error rate, computational performance or light efficiency. We propose an optical setup to be placed in front of the binary SLM and the associated signal processing algorithm. The proposed system uses a 4-f setup and a periodic mask is placed to the Fourier plane. As a result, the binary SLM is convolved with a series of regularly spaced impulse functions and we get a new SLM which is smaller in pixel count compared to binary SLM but which can provide 16-bit full complex modulation. It becomes easier to generate the desired light field with this new SLM. Also, the required computations are carried out in a fast manner to enable real-time operation. ©2010 IEEE.
Open Access
A tree-based solution to nonlinear regression problem
(IEEE, 2016) Demir, Oğuzhan; Neyshabouri, Mohammadreza Mohaghegh; Delibalta, İ.; Kozat, Süleyman Serdar
In this paper, we offer and examine a new algorithm for sequential nonlinear regression problem. In this architecture, we use piecewise adaptive linear functions to find the nonlinear regression model sequentially. For more accurate and faster convergence, we combine a large class of piecewise linear functions. These piecewise linear functions are constructed by composing different adaptive linear functions, which are represented by the nodes of a lexicographical tree. With this tree structure, computational complexity of the algorithm is significantly reduced. To show the performance of the proposed algorithm, we present a simulation which is performed by using a well-known real data set.