Firefly algorithm (FA) is a new meta-heuristic optimisation algorithm that mimics the social behaviour of fireflies flying in the tropical and temperate summer sky. In this study, a novel application of FA is presente...
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Firefly algorithm (FA) is a new meta-heuristic optimisation algorithm that mimics the social behaviour of fireflies flying in the tropical and temperate summer sky. In this study, a novel application of FA is presented as it is applied to solve tracking problem. A general optimisation-based tracking architecture is proposed and the parameters' sensitivity and adjustment of the FA in tracking system are studied. Experimental results show that the FA-based tracker can robustly track an arbitrary target in various challenging conditions. The authors compare the speed and accuracy of the FA with three typical tracking algorithms including the particle filter, meanshift and particle swarm optimisation. Comparative results show that the FA-based tracker outperforms the other three trackers.
Closed-loop identification of continuous systems, which can be considered as a nonlinear optimization problem, may result in a difficult solution problem when conventional methods are used. In this paper it is present...
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Closed-loop identification of continuous systems, which can be considered as a nonlinear optimization problem, may result in a difficult solution problem when conventional methods are used. In this paper it is presented a hybrid strategy based on an Adaptive Genetic Algorithm and the Simplex method, that results in a satisfactory solution for this problem. The proposal is compared with other techniques reported in the literature. Three examples show the performance of the method: identification of high order dynamics;identification of unstable second order dynamics in open-loop;and parameter estimation in power generation systems. Simulation results show that the proposed is a robust method for close-loop system identification.
In this paper we propose a new algorithm for fast l(1) minimization as frequently arising in compressed sensing. Our method is based on a split Bregman algorithm applied to the dual of the problem of minimizing parall...
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In this paper we propose a new algorithm for fast l(1) minimization as frequently arising in compressed sensing. Our method is based on a split Bregman algorithm applied to the dual of the problem of minimizing parallel to u parallel to(1) + 1/2 alpha parallel to u parallel to(2) such that u solves the under-determined linear system Au = f, which was recently investigated in the context of linearized Bregman methods. Furthermore, we provide a convergence analysis for split Bregman methods in general and show with our compressed sensing example that a split Bregman approach to the primal energy can lead to a different type of convergence than split Bregman applied to the dual, thus making the analysis of different ways to minimize the same energy interesting for a wide variety of optimization problems.
The light weight deflectometer (LWD) is a portable, nondestructive testing device that can estimate pavement layer parameters, namely moduli. Conventional backcalculation of layer parameters from LWD deflections is fo...
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The light weight deflectometer (LWD) is a portable, nondestructive testing device that can estimate pavement layer parameters, namely moduli. Conventional backcalculation of layer parameters from LWD deflections is formulated as an inverse problem where predicted vertical deflections are matched to observed vertical deflections using a gradient search algorithm. In this paper, we present an LWD backcalculation scheme to recover layer parameters, including top-layer thickness, of a two-layer earthwork system. Our approach resolves the problem using a dynamic finite-element (FE) model for the forward calculation of LWD deflection data and implements a genetic algorithm (GA) as the inverse solver. The objective function we minimize is formulated as a measure of the data misfit between predicted and observed data, normalized by the peak deflections, and it includes 180 data points from the dynamic deflection time history. The objective function contains multiple local minima that can potentially trap gradient search algorithms, thus validating application of GA as a global search technique for this problem. The GA is applied to both synthetic and experimental data, and we demonstrate that the recovered top-layer thickness, top-layer modulus, and underlying modulus for the experimental data compare favorably with expected values. (C) 2013 American Society of Civil Engineers.
For extremely high-performance lithographic lenses, the edge level accuracy of the manufacturing process and multicompensation strategies must be applied. Element clocking can be effectively used to compensate for the...
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For extremely high-performance lithographic lenses, the edge level accuracy of the manufacturing process and multicompensation strategies must be applied. Element clocking can be effectively used to compensate for the low-order figure errors of the elements. Considering that commercial optical software is usually incapable of obtaining good convergence for clocking optimization, this paper proposes a mathematical model of a lithographic lens containing the errors of a surface figure, after which a clocking optimization algorithm is programmed. A clocking optimization instance proving that the clocking optimization algorithm is capable of finding the optimized angle of elements and that clocking is an effective compensation strategy. The calculated accuracy of the proposed mathematic model was found to be acceptable for clocking optimization. (C) 2013 Optical Society of America
This paper presents a new method for finding two link-disjoint paths in WDM networks under wavelength continuity and lowest cost constraints. Such a problem is considered to be an NP-complete problem, which is only so...
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This paper presents a new method for finding two link-disjoint paths in WDM networks under wavelength continuity and lowest cost constraints. Such a problem is considered to be an NP-complete problem, which is only solvable using Integer Linear Programming (ILP). The presented method is based on transforming the original network into an auxiliary network with n x n nodes and 2 mn links, where n is the number of nodes and m is the number of links in the original network, and then applying a modified version of Dijkstra's shortest path algorithm on that network. Despite the larger network size, the execution time of the algorithm is in polynomial order. Considering that the problem is NP-complete, the presented algorithm takes much less time than using ILP, which generally requires exponential time. Yet, it is able to find all available disjoint paths obtainable by ILP.
The number of available algorithms for the so-called Basis Pursuit Denoising problem (or the related LASSO-problem) is large and keeps growing. Similarly, the number of experiments to evaluate and compare these algori...
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The number of available algorithms for the so-called Basis Pursuit Denoising problem (or the related LASSO-problem) is large and keeps growing. Similarly, the number of experiments to evaluate and compare these algorithms on different instances is growing. In this correspondence, we present a method to produce instances with exact solutions that is based on a simple observation, related to the so-called source condition from sparse regularization.
This work presents a methodology for identifying inclusions in a conductor domain. The methodology is based on electrical potential measurements on the external boundary of a conductor body subjected to a prescribed s...
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This work presents a methodology for identifying inclusions in a conductor domain. The methodology is based on electrical potential measurements on the external boundary of a conductor body subjected to a prescribed set of electrical current injections. The boundary of each inclusion is approximated by a special kind of spline, whose control points have an extra parameter related to the distance between the control point and the curve. Such special feature allows identification of smooth or sharp inclusions with the same initial guess. The identification is an inverse problem that, in this work, is solved by the Levenberg-Marquardt Method. This iterative method tries to locate the minimum of an objective function, the square of the norm of a residual vector function, given by the differences between electrical potential measurements and the computed ones. The computation of the electrical potential is called forward problem and it is solved by an implementation of the direct formulation of the Boundary Element Method (BEM). The present paper addresses two approaches for computing the derivatives of the residual function with respect to the minimization parameters, required by the Levenberg-Marquardt Method. The first one is based on finite differences and the second one is based on the direct differentiation of the integral equation of the BEM for potential problems. Performance comparisons of these two approaches are presented, based on numerical experiments of identification of inclusions with noisy datasets computationally obtained. (C) 2013 Elsevier Ltd. All rights reserved.
It is seemingly paradoxical to the classical definition of the independent component analysis (ICA), that in reality, the true sources are often not strictly uncorrelated. With this in mind, this letter concerns a fra...
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It is seemingly paradoxical to the classical definition of the independent component analysis (ICA), that in reality, the true sources are often not strictly uncorrelated. With this in mind, this letter concerns a framework to extract quasi-uncorrelated sources with finite supports by optimizing a range-based contrast function under unit-norm constraints (to handle the inherent scaling indeterminacy of ICA) but without orthogonality constraints. Albeit the appealing contrast properties of the range-based function (e.g., the absence of mixing local optima), the function is not differentiable everywhere. Unfortunately, there is a dearth of literature on derivative-free optimizers that effectively handle such a nonsmooth yet promising contrast function. This is the compelling reason for the design of a nonsmooth optimization algorithm on a manifold of matrices having unit-norm columns with the following objectives: to ascertain convergence to a Clarke stationary point of the contrast function and adhere to the necessary unit-norm constraints more naturally. The proposed nonsmooth optimization algorithm crucially relies on the design and analysis of an extension of the mesh adaptive direct search (MADS) method to handle locally Lipschitz objective functions defined on the sphere. The applicability of the algorithm in the ICA domain is demonstrated with simulations involving natural, face, aerial, and texture images.
In this paper the inverse problem of electrical impedance tomography (ELT) in a three dimensional environment is considered. In this technique, electrodes are placed on the external boundary of the body and electrical...
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In this paper the inverse problem of electrical impedance tomography (ELT) in a three dimensional environment is considered. In this technique, electrodes are placed on the external boundary of the body and electrical current is injected by sequentially activating pairs of them while the corresponding potentials are measured. Usually such measures are used in order to solve the nonlinear inverse problem of achieving a two-dimensional image of the conductivity distribution over the cross section of the body. In the problem studied here the goal is to determine the size and position of an existing cavity within a homogeneous medium. The geometrical parameters that describe the cavities are the unknowns of the resulting 3D inverse problem, which is solved by the Levenberg-Marquardt method. Two shapes of geometrical cavities are here considered: spherical and spheroidal. Due to its accuracy and simplicity of mesh generation, the Boundary Element Method (BEM) is used in the solution of the direct problem. In order to evaluate the proposed strategy, numerical experiments are presented varying the position and the shape of the cavity and also the injection-measure protocol used. Since measured data are not currently available, boundary potential measurements have been obtained computationally also using BEM. The sensitivity of the present method in the presence of measurement noise has also been estimated through numerical experiments. (C) 2013 Elsevier Ltd. All rights reserved.
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