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22nd IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Noureddine, Hadi Castelain, Damien Pyndiah, Ramesh Mitsubishi Electric R&D Centre Europe France

ISBN: (纸本)9781457713484

In cooperative localization, the aim is to compute the locations in Euclidean space of a set of nodes performing pair-wise distance measurements. In cases of lack of measurements, several nodes might have multiple feasible solutions meeting the distance constraints. In this paper, we are interested in identifying the nodes that have a unique solution. By employing a semidefinite programming (SDP) formulation of the problem, it is possible to identify only a portion of the uniquely solvable nodes. To improve the identification of these nodes, we develop an iterative algorithm based on SDP. At each iteration, the objective function of the SDP problem is modified in order to identify additional uniquely solvable nodes. We apply this algorithm to study the statistical occurrence of uniquely solvable nodes in uniformly generated networks, and compare the results with the simple SDP. We also investigate the errors in the computed locations for both methods and a variant of the SDP method augmented by bounding constraints on unobserved distances.

关键词： Euclidean space SDP method SDP problem cooperative communication cooperative localization cooperative network localizability distance constraint distance measurement iterative algorithm iterative methods mathematical programming multiple feasible solution pairwise distance measurement semidefinite programming statistical analysis statistical occurrence

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Weighted Sum Rate Maximization in the Underlay Cognitive MISO Interference Channel

Weighted Sum Rate Maximization in the Underlay Cognitive MIS...

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22nd IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Gallo, Laurent Negro, Francesco Ghauri, Irfan Slock, Dirk T. M. Politecn Torino 24 Corso Duca Abruzzi I-10129 Turin Italy GAIA Intel Mobile Commun F-06560 Sophia Antipolis France EURECOM Mobile Commun Dept F-06904 Sophia Antipolis France

ISBN: (纸本)9781457713484

In this paper we address the problem of Weighted Sum Rate (WSR) maximization for a K-user Multiple-Input Single-Output (MISO) cognitive Interference Channel (IFC) with linear transmit beamforming (BF) vectors in an underlay cognitive radio setting. We consider a set of L single-antenna Primary receivers to which the cognitive system can causes a limited amount of interference. We thus propose an iterative algorithm to determine the BF vectors for the secondary transmission. The optimization of the Lagrange multipliers involved in the optimization problem is based on the subgradient method. The expression of the BF vector can be interpreted as dual Uplink (UL) MMSE receiver that takes into account the interference caused by a fictitious link between the primary user and secondary base station. Finally Deterministic Annealing is applied to make the convergence of the algorithm easier.

关键词： BF vector Convergence Interference K-user multiple-input single-output L single-antenna primary receiver Lagrange multiplier MISO cognitive interference channel MMSE receiver Noise Optimization Receivers Strontium Vectors WSR maximization antennas array signal processing cognitive radio cognitive radio cognitive system deterministic annealing iterative algorithm iterative methods linear transmit beamforming mean square error methods primary user radio receivers radiofrequency interference secondary base station underlay cognitive MISO interference channel uplink weighted sum rate maximization wireless channels

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Minimal state variable solutions to Markov-switching rational expectations models

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JOURNAL OF ECONOMIC DYNAMICS & CONTROL 2011年第12期35卷 2150-2166页

作者： Farmer, Roger E. A. Waggoner, Daniel F. Zha, Tao Emory Univ Fed Reserve Bank Atlanta UCLA Atlanta GA 30322 USA

We develop a new method for deriving minimal state variable (MSV) equilibria of a general class of Markov switching rational expectations models and a new algorithm for computing these equilibria. We compare our approach to previously known algorithms, and we demonstrate that ours is both efficient and more reliable than previous methods in the sense that it is able to find MSV equilibria that previously known algorithms cannot. Further, our algorithm can find all possible MSV equilibria in models. This feature is essential if one is interested in using a likelihood based approach to estimation. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Multiple MSV equilibria Policy changes Likelihood principle Quadratic polynomial E-stability iterative algorithm

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A novel Preconditioned Conjugate Gradient Image Reconstruction algorithm For Electrical Capacitance Tomography System

A novel Preconditioned Conjugate Gradient Image Reconstructi...

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International Conference on Materials Science and Technology

作者： Chen Yu Cao Jun Chen Deyun NE Forestry Univ Mech Engn Postdoctoral Res Stn Harbin Peoples R China Comp Inst Harbin Univ Sci & Technol Harbin Peoples R China

ISBN: (纸本)9783037850152

To solve the 'soft-field' nature and the ill-posed problem in electrical capacitance tomography (ECT)technology, a novel preconditioned conjugate gradient algorithm for electrical capacitance tomography is presented. The analysis of the basic principles of electrical capacitance tomography, based on the given preconditioned conjugate gradient method and calculation formula of the iteration steps of the ECT and to explore the feasibility of application of the algorithm, the algorithm to meet the convergence conditions and the reconstruction image error. Experimental results and simulation data indicate that the algorithm can provide high quality images and favorable stabilization compared with LBP, conjugate gradient algorithms in simple flow pattern and this new algorithm presents a feasible and effective way to research on image reconstruction algorithm for Electrical Capacitance Tomography System.

关键词： electrical capacitance tomography image reconstruction iterative algorithm conjugate gradient

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DYNAMICAL MODEL FOR EVOLUTION OF ROCK MASSIVE STATE AS A RESPONSE ON A CHANGING OF STRESS-DEFORMED STATE

DYNAMICAL MODEL FOR EVOLUTION OF ROCK MASSIVE STATE AS A RES...

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3rd International Conference on Heterogeneous Material Mechanics (ICHMM 2011)

作者： Hachay, O. A. Khachay, A. Y. Inst Geophys UB RAS Ekaterinburg 620016 Russia Ural State Univ Ekaterinburg 620000 Russia

ISBN: (纸本)9781605950549

For research of the medium response with hierarchic structure we had developed an iterative algorithm for electromagnetic and seismic fields in the problem setting similar to analyzed higher for layered-block models with homogeneous inclusions. From the received results we did a conclusion, that the higher the rank of hierarchy of the medium the hardly diminishes the similarity between seismic and electromagnetic results, and the obtained information has a nondependent sense, which underlines the complexity of the researched medium.

关键词： Hierarchic medium structure iterative algorithm seismic and electromagnetic fields

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Some iterative algorithms for the obstacle problems

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2010年第11期87卷 2493-2502页

作者： Lian, Xiao-Peng Cen, Zhongdi Cheng, Xiao-Liang Zhejiang Wanli Univ Inst Math Ningbo Zhejiang Peoples R China Zhejiang Univ Dept Math Hangzhou 310003 Zhejiang Peoples R China

In this paper we propose some iterative algorithms for the obstacle problems discretized by the finite difference method. We rewrite the obstacle problem to an equivalent complementarity problem. We use the regularization trick to non-smooth absolute function. Then we apply the Newton's method to obtain an iterative algorithm. Some other two algorithms based on this algorithm are derived. Numerical experiments show the effective of the algorithm.

关键词： obstacle problem iterative algorithm complementarity problem finite difference monotone iteration

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Scaling iterative closest point algorithm for registration of m-D point sets

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2010年第5-6期21卷 442-452页

作者： Du, Shaoyi Zheng, Nanning Xiong, Lei Ying, Shihui Xue, Jianru Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian 710049 Peoples R China AF Engn Univ Sch Engn Xian 710049 Peoples R China Shanghai Univ Sch Sci Dept Math Shanghai 200444 Peoples R China

Point set registration is important for calibration of multiple cameras, 3D reconstruction and recognition, etc. The iterative closest point (ICP) algorithm is accurate and fast for point set registration in a same scale, but it does not handle the case with different scales. This paper instead introduces a novel approach named the scaling iterative closest point (SICP) algorithm which integrates a scale matrix with boundaries into the original ICP algorithm for scaling registration. At each iterative step of this algorithm, we set up correspondence between two m-D point sets, and then use a simple and fast iterative algorithm with the singular value decomposition (SVD) method and the properties of parabola incorporated to compute scale, rotation and translation transformations. The SICP algorithm has been proved to converge monotonically to a local minimum from any given parameters. Hence, to reach desired global minimum, good initial parameters are required which are successfully estimated in this paper by analyzing covariance matrices of point sets. The SICP algorithm is independent of shape representation and feature extraction, and thereby it is general for scaling registration of m-D point sets. Experimental results demonstrate its efficiency and accuracy compared with the standard ICP algorithm. (C) 2010 Elsevier Inc. All rights reserved.

关键词： iterative closest point (ICP) Singular value decomposition (SVD) Properties of parabola Scaling registration Point set registration iterative algorithm Local convergence Covariance matrix

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Gradient based and least squares based iterative algorithms for matrix equations AXB plus CX^TD = F

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APPLIED MATHEMATICS AND COMPUTATION 2010年第5期217卷 2191-2199页

作者： Xie, Li Liu, Yanjun Yang, Huizhong Jiangnan Univ Control Sci & Engn Res Ctr Wuxi 214122 Peoples R China

This paper develops a gradient based and a least squares based iterative algorithms for solving matrix equation AXB + (CXD)-D-T = F. The basic idea is to decompose the matrix equation (system) under consideration into two subsystems by applying the hierarchical identification principle and to derive the iterative algorithms by extending the iterative methods for solving Ax = b and AXB = F. The analysis shows that when the matrix equation has a unique solution (under the sense of least squares), the iterative solution converges to the exact solution for any initial values. A numerical example verifies the proposed theorems. (C) 2010 Elsevier Inc. All rights reserved.

关键词： iterative algorithm Gradient search Least squares Lyapunov matrix equations Sylvester matrix equations

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Solvability and convergence of iterative algorithms for certain functional equations arising in dynamic programming

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OPTIMIZATION 2010年第6期59卷 887-916页

作者： Liu, Zeqing Kang, Shin Min Ume, Jeong Sheok Liaoning Normal Univ Dept Math Dalian 116029 Liaoning Peoples R China Gyeongsang Natl Univ Dept Math Jinju 660701 South Korea Gyeongsang Natl Univ Res Inst Nat Sci Jinju 660701 South Korea Changwon Natl Univ Dept Appl Math Chang Won 641773 South Korea

In this article, we introduce and study the following functional equation arising in dynamic programming of multistage decision processes: [image omitted] In order to solve the functional equation, we suggest some iterative algorithms. Under certain conditions we give a few sufficient conditions ensuring both the existence and uniqueness of solution for the functional equation and the convergence of these iterative algorithms with respect to the solution. We investigate also properties of nonpositive solutions and nonnegative solutions for several functional equations which are special cases of the above mentioned functional equation. To illustrate the results presented in this article, we construct eight nontrivial examples.

关键词： dynamic programming functional equation solution nonpositive solution nonnegative solution nonexpansive mapping Banach fixed-point theorem iterative algorithm

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Efficient iterative algorithm for phase-shifting interferometry

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OPTICS AND LASERS IN ENGINEERING 2007年第2期45卷 281-292页

作者： Guo, Hongwei Zhao, Zhan Chen, Mingyi Shanghai Univ Lab Appl Opt & Metrol Shanghai 200072 Peoples R China

This paper presents an efficient iterative least-squares algorithm for phase-shifting interferometry. If the phase shifts contain errors, the residuals (i.e. the differences between the recorded intensities and their recalculated values) of least-squares algorithm are dependent on these errors. Based on this fact, an approach that allows estimating the phase shift errors from these residuals is derived. Using the results, the values of phase shifts are corrected. By iterating the two steps: phase evaluation and phase shift correction, the phase distribution can be accurately reconstructed. Its validity and performances have been investigated by both the numerical simulation and experiment results. The convergence condition with this algorithm is also discussed. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： interferometry phase measurement phase-shifting algorithm iterative algorithm

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