In this paper, the linear mapping from the constrained solution sets to their independent parameter spaces is constructed, and its properties are studied. Based on these properties and the classical algorithm LSQR...
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In this paper, the linear mapping from the constrained solution sets to their independent parameter spaces is constructed, and its properties are studied. Based on these properties and the classical algorithm LSQR for solving the (unconstrained) LS problem, a matrix iterative method that can find the special centrosymmetric solution is proposed. Numerical results are reported that show the efficiency of the proposed method.
Clock synchronization is a well-studied problem with many practical and scientific *** propose an arbitrary accuracy iterative quantum algorithm for distributed clock synchronization using only three *** n bits of the...
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Clock synchronization is a well-studied problem with many practical and scientific *** propose an arbitrary accuracy iterative quantum algorithm for distributed clock synchronization using only three *** n bits of the time difference between two spatially separated clocks can be deterministically extracted by communicating only O（n） messages and executing the quantum iteration process n times based on the classical feedback and measurement ***,we also give the algorithm using only two qubits and discuss the success probability of the algorithm.
This study investigates a new delivery problem that has emerged after the attempts of several e-commerce and logistics firms to deploy drones in their operations to increase efficiency and reduce delivery times. In th...
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This study investigates a new delivery problem that has emerged after the attempts of several e-commerce and logistics firms to deploy drones in their operations to increase efficiency and reduce delivery times. In this problem, a delivery truck that carries a drone on its roof serves customers in coordination with a drone. The drone is considered to complement the truck due to its cost-efficiency and ability to access difficult terrains and to travel without exposure to congestion. This study presents an iterative algorithm that is based on a decomposition approach to minimize delivery completion time. In the first stage of the proposed methodology, the truck route and the customers assigned to the drone are determined. In the second stage, a mixed integer linear programming model is solved to optimize the drone route by fixing the routing and the assignment decisions that are made in the first stage. Beginning with the shortest truck route, the assignment and the routing decisions are iteratively improved. The solution times of our algorithm are compared with the solution times of the state-of-the-art formulations that are solved by CPLEX. The results demonstrate that our algorithm yields shorter solution times for the instances that we generated with the specified parameters. An optimization-based heuristic algorithm, which obtains solutions for medium-sized instances, is developed by reducing the feasible search area.
In order to assess a large number of diverse projects as fairly and rapidly as possible, a procedure often adopted is to use a panel consisting of a large number of experts, only a small number of whom assess each pro...
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In order to assess a large number of diverse projects as fairly and rapidly as possible, a procedure often adopted is to use a panel consisting of a large number of experts, only a small number of whom assess each project. Since no one expert assesses all the projects, conscious or unconscious bias regarding overall standards by any expert will advantage or disadvantage the projects assessed by that particular expert. This paper presents an iterative algorithm that has been used successfully to detect and correct for such biases. Each expert's assessments are modeled as differing from the ideal as a result of a shift of mean and having a standard deviation that is too low or too high. This model is used in conjunction with the concept of "paired assessments" to account for individual projects being of unusually high or low quality and so to evaluate the discrepancy from the ideal marks. The same computer program also has applications in the peer-review or expert-evaluation of research proposals, and any other situation involving subjective assessments by a restricted number of persons.
Terahertz time-domain spectroscopy is a specifically appropriated technique to analyze layered structure composition and dimension. Inverse electromagnetic problems are commonly solved to extract, from a recorded tera...
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Terahertz time-domain spectroscopy is a specifically appropriated technique to analyze layered structure composition and dimension. Inverse electromagnetic problems are commonly solved to extract, from a recorded terahertz-signal, the distinctive layer dielectric properties and thicknesses. However, main origins and formation routes of the signal are left unassessed while it could be of great value to deepen and to enlarge stratified material terahertz-probing property knowledge and understanding. In this article, a new numerical method to reconstruct and to analyze terahertz experimental signals is reported. It consists of an iterative algorithm implementing a connected propagation tree where each node of the tree denotes the occurrence of the incident pulse division. Descendent pulses are individually monitored and their carried proportion of the incident power can be evaluated. Therefore, it provides a flowchart of the predominant optical paths contributing to the structure response. On this basis, a simplified global transfer function is automatically derived by the algorithm. The effectiveness of the numerical procedure is demonstrated through the reconstruction and the analysis of a reflected terahertz-signal from an aerospace coating structure with individual and different thicknesses of several tens of microns. The recovered signal is first discussed as a function of the sum of pulses detected at each iteration. Then, the power proportion distribution for each iteration is studied to delimit the meaningful number of required algorithm iteration. Finally, within each iteration are sorted the most contributing optical paths and a simplified global transfer function is derived. The present algorithm allowed to identify the main propagations inside this stratified material giving arise to the recorded signal and to reduce by ${\text{98.23}}\%$ the number of considered and calculated optical paths compared to the standard signal reconstruction procedure.
In this paper, the auxiliary principle technique is extended to study a system of generalized nonlinear mixed quasivariational-like inequalities in Hilbert spaces. First, we establish the existence of solutions of the...
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In this paper, the auxiliary principle technique is extended to study a system of generalized nonlinear mixed quasivariational-like inequalities in Hilbert spaces. First, we establish the existence of solutions of the corresponding system of auxiliary generalized nonlinear mixed qusi-variational-like inequalities. Then based on the existence result, we construct a new iterative algorithm. Finally, both the existence of solutions of the original problem and the convergence of iterative sequences generated by the algorithm are proved. Our results improve and extend some known results.
作者：
Zolfaghari, ALASSI-GRSM
Université de Reims Champagne Ardenne BP 347 F51062 Reims Cedex France
An X-ray microtomograph has been built in our laboratory from a conventional scanning electron microscope. An algorithm based on Algebraic Reconstruction Techniques (ART) has been developed to reconstruct the internal...
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An X-ray microtomograph has been built in our laboratory from a conventional scanning electron microscope. An algorithm based on Algebraic Reconstruction Techniques (ART) has been developed to reconstruct the internal structure of the imaged object. This algorithm takes into account the diverging nature of the X-ray beam. In this paper we explain the reconstruction algorithm and we analyse the quality of the reconstructed objects in terms of signal-to-noise ratio (SNR), spatial resolution and cross-entropy.
In this paper,by introducing a tuning parameter,an explicit iterative algorithm is constructed for solving the continuous Lyapunov matrix equations associated with It? stochastic systems.A necessary and sufficient con...
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In this paper,by introducing a tuning parameter,an explicit iterative algorithm is constructed for solving the continuous Lyapunov matrix equations associated with It? stochastic systems.A necessary and sufficient condition is provided to guarantee the convergence of the proposed algorithm by using the Kronecker ***,some easily verifiable convergence results are developed for the proposed algorithm based on the obtained necessary and sufficient *** addition,a method is given for the selection of the optimal tuning ***,an example is applied to verify the effectiveness of the presented algorithm.
In this paper, we employ the auxiliary principle technique to study a generalized nonlinear mixed quasi-variational-like inequality in Hilbert spaces. Fist, we establish the existence and uniqueness of solution of the...
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In this paper, we employ the auxiliary principle technique to study a generalized nonlinear mixed quasi-variational-like inequality in Hilbert spaces. Fist, we establish the existence and uniqueness of solution of the corresponding auxiliary generalized nonlinear mixed quasi-variational-like inequality by making use of minimizing sequence of a convex function. Then based on the existence result, we construct an iterative algorithm for finding approximate solution to the exact solution of the generalized nonlinear mixed quasi-variational-like inequality. Our results extend, improve and unify some known results in the literature.
A two-stage least squares based iterative (two-stage LSI) identification algorithm is derived for controlled autoregressive moving average (CARMA) systems. The basic idea is to decompose a CARMA system into two subsys...
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A two-stage least squares based iterative (two-stage LSI) identification algorithm is derived for controlled autoregressive moving average (CARMA) systems. The basic idea is to decompose a CARMA system into two subsystems and to identify each subsystem, respectively. Because the dimensions of the involved covariance matrices in each subsystem become small, the proposed algorithm has a high computational efficiency. The simulation results indicate that the proposed algorithm is effective. (C) 2011 Elsevier Ltd. All rights reserved.
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