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An iterative method for updating gyroscopic systems based on measured modal data

APPLIED MATHEMATICS AND COMPUTATION 2011年第7期218卷 3753-3762页

作者： Yuan, Yongxin Jiangsu Univ Sci & Technol Sch Math & Phys Zhenjiang 212003 Peoples R China

An efficient iterative method for updating the mass, gyroscopic and stiffness matrices simultaneously using a few of complex measured modal data is developed. By using the proposed iterative method, the unique symmetric solution can be obtained within finite iteration steps in the absence of roundoff errors by choosing a special kind of initial matrices. Numerical results show that the presented method can be used to update finite element models to get better agreement between analytical and experimental modal parameters. (C) 2011 Elsevier Inc. All rights reserved.

关键词： Model updating iterative algorithm Gyroscopic system Partially prescribed spectral data Optimal approximation

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Positivity-preserving H_∞ model reduction for positive systems

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AUTOMATICA 2011年第7期47卷 1504-1511页

作者： Li, Ping Lam, James Wang, Zidong Date, Paresh Univ Hong Kong Dept Mech Engn Hong Kong Hong Kong Peoples R China Brunel Univ Dept Informat Syst & Comp Uxbridge UB8 3PH Middx England Brunel Univ Dept Math Sci Uxbridge UB8 3PH Middx England

This paper is concerned with the model reduction of positive systems. For a given stable positive system, our attention is focused on the construction of a reduced-order model in such a way that the positivity of the original system is preserved and the error system is stable with a prescribed H-infinity performance. Based upon a system augmentation approach, a novel characterization on the stability with H-infinity performance of the error system is first obtained in terms of linear matrix inequality (LMI). Then, a necessary and sufficient condition for the existence of a desired reduced-order model is derived accordingly. Furthermore, iterative LMI approaches with primal and dual forms are developed to solve the positivity-preserving H-infinity model reduction problem. Finally, a compartmental network is provided to show the effectiveness of the proposed techniques. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： H-infinity performance iterative algorithm Linear matrix inequality Model reduction Positive systems

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Graph convergence for the H(.,.)-accretive operator in Banach spaces with an application

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APPLIED MATHEMATICS AND COMPUTATION 2011年第22期217卷 9053-9061页

作者： Li, Xi Huang, Nan-jing Sichuan Univ Dept Math Chengdu 610064 Sichuan Peoples R China

In this paper, a concept of graph convergence concerned with the H(.,.)-accretive operator is introduced in Banach spaces and some equivalence theorems between of graph-convergence and resolvent operator convergence for the H(.,.)-accretive operator sequence are proved. As an application, a perturbed algorithm for solving a class of variational inclusions involving the H(.,.)-accretive operator is constructed. Under some suitable conditions, the existence of the solution for the variational inclusions and the convergence of iterative sequence generated by the perturbed algorithm are also given. (C) 2011 Elsevier Inc. All rights reserved.

关键词： H(.,.)-accretive operator Graph convergence Resolvent operator Variational inclusion iterative algorithm Convergence

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Cyclic algorithms for split feasibility problems in Hilbert spaces

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NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS 2011年第12期74卷 4105-4111页

作者： Wang, Fenghui Xu, Hong-Kun Natl Sun Yat Sen Univ Dept Appl Math Kaohsiung 80424 Taiwan Luoyang Normal Univ Dept Math Luoyang 471022 Peoples R China King Saud Univ Coll Sci Dept Math Riyadh 11451 Saudi Arabia

The split common fixed point problem (SCFPP) is equivalently converted to a common fixed point problem of a finite family of class-T operators. This enables us to introduce new cyclic algorithms to solve the SCFPP and... 详细信息

关键词： Convex feasibility Split feasibility Split common fixed point Nonexpansive mapping Class-T operator iterative algorithm

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Robust linear transceivers for downlink multi-user multiple-input multiple-output systems using second-order cone programming optimisation

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IET COMMUNICATIONS 2011年第17期5卷 2586-2593页

作者： Li, H. Xie, S. Northeastern Univ Coll Informat Sci & Engn Shenyang 110006 Liaoning Peoples R China Inst Infocomm Res Singapore 138632 Singapore

This study addresses the joint robust linear transceiver design problems for a downlink multi-user multiple-input multiple-output (MIMO) antenna system in the presence of imperfect channel state information (CSI). The uncertainty in the channel is characteried by a norm-bounded region, and two robust optimal design problems are considered. One is aimed at minimising the total transmitter power subject to users' mean square error (MSE) constraints in the presence of channel uncertainty, the other is to minimise the worst-case sum-mean square error (sum-MSE) under power constraints for all admissible uncertainties. For these two problems, the authors propose two iterative algorithms based on second-order cone programming (SOCP) formulations, which can be efficiently solved and have less computational complexity than their semi-definite programming (SDP) counterparts. Simulation results also illustrate that the proposed robust design approaches can significantly reduce the computational complexity while achieving almost the same performance as the robust SDP methods.

关键词： convex programming norm-bounded region sum-MSE Optimisation techniques robust linear transceiver wireless channels worst-case sum-mean square error iterative methods semidefinite programming robust optimal design problem iterative algorithm mean square error methods Single antennas robust SDP method radio transceivers channel uncertainty downlink multiuser multiple-input multiple-output antenna system Interpolation and function approximation (numerical analysis) imperfect channel state information computational complexity Radio links and equipment second-order cone programming optimisation antennas power constraint MIMO communication

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Fast Model-Based X-Ray CT Reconstruction Using Spatially Nonhomogeneous ICD Optimization

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2011年第1期20卷 161-175页

作者： Yu, Zhou Thibault, Jean-Baptiste Bouman, Charles A. Sauer, Ken D. Hsieh, Jiang Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA Univ Notre Dame Dept Elect Engn Notre Dame IN 46556 USA GE Healthcare Technol Waukesha WI 53188 USA

Recent applications of model-based iterative reconstruction (MBIR) algorithms to multislice helical CT reconstructions have shown that MBIR can greatly improve image quality by increasing resolution as well as reducing noise and some artifacts. However, high computational cost and long reconstruction times remain as a barrier to the use of MBIR in practical applications. Among the various iterative methods that have been studied for MBIR, iterative coordinate descent (ICD) has been found to have relatively low overall computational requirements due to its fast convergence. This paper presents a fast model-based iterative reconstruction algorithm using spatially nonhomogeneous ICD (NHICD) optimization. The NH-ICD algorithm speeds up convergence by focusing computation where it is most needed. The NH-ICD algorithm has a mechanism that adaptively selects voxels for update. First, a voxel selection criterion VSC determines the voxels in greatest need of update. Then a voxel selection algorithm VSA selects the order of successive voxel updates based upon the need for repeated updates of some locations, while retaining characteristics for global convergence. In order to speed up each voxel update, we also propose a fast 1-D optimization algorithm that uses a quadratic substitute function to upper bound the local 1-D objective function, so that a closed form solution can be obtained rather than using a computationally expensive line search algorithm. We examine the performance of the proposed algorithm using several clinical data sets of various anatomy. The experimental results show that the proposed method accelerates the reconstructions by roughly a factor of three on average for typical 3-D multislice geometries.

关键词： Computed tomography coordinate descent iterative algorithm model based iterative reconstruction (MBIR)

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Image segmentation by iterative optimization of multiphase multiple piecewise constant model and Four-Color relabeling

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PATTERN RECOGNITION 2011年第12期44卷 2819-2833页

作者： Liu, Liman Tao, Wenbing Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Inst Pattern Recognit & Artificial Intellegence Wuhan 430074 Peoples R China

In the paper an iteratively unsupervised image segmentation algorithm is developed, which is based on our proposed multiphase multiple piecewise constant (MMPC) model and its graph cuts optimization. The MMPC model use multiple constants to model each phase instead of one single constant used in Chan and Vese (CV) model and cartoon limit so that heterogeneous image object segmentation can be effectively dealt with. We show that the multiphase optimization problem based on our proposed model can be approximately solved by graph cuts methods. Four-Color theorem is used to relabel the regions of image after every iteration, which makes it possible to represent and segment an arbitrary number of regions in image with only four phases. Therefore, the computational cost and memory usage are greatly reduced. The comparison with some typical unsupervised image segmentation methods using a large number of images from the Berkeley Segmentation Dataset demonstrates the proposed algorithm can effectively segment natural images with a good performance and acceptable computational time. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Unsupervised image segmentation Multiphase optimization Four-Color relabeling iterative algorithm Mean shift

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Projection algorithms for the system of mixed variational inequalities in Banach spaces

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MATHEMATICAL AND COMPUTER MODELLING 2011年第9-10期53卷 1692-1699页

作者： Zhang, Qing-bang Deng, Ruliang Liu, Liu SW Univ Finance & Econ Coll Econ Math Chengdu 610074 Sichuan Peoples R China Sichuan Univ Arts & Sci Dept Math Dazhou 635000 Sichuan Peoples R China

In this paper, the system of mixed variational inequalities is introduced and considered in Banach spaces, which includes some known systems of variational inequalities and the classical variational inequalities as special cases. Using the projection operator technique, we suggest some iterative algorithms for solving the system of mixed variational inequalities and prove the convergence of the proposed iterative methods under suitable conditions. Our theorems generalize some known results shown recently. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： System of mixed variational inequalities Projection operator iterative algorithm Convergence

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Design of halfband filters for orthonormal wavelets using ripple-pinning

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IET SIGNAL PROCESSING 2011年第1期5卷 40-48页

作者： Tay, D. B. H. La Trobe Univ Dept Elect Engn Bundoora Vic 3086 Australia

The design of halfband filters for orthonormal wavelet with a prescribed number of vanishing moment and prescribed ripple amplitudes is described. The technique is an extension of the zero-pinning (ZP) technique and is called ripple-pinning (RP). In ZP, the positions of stopband minima (of a Bernstein polynomial) are specified explicitly and the stopband maxima (position and amplitude) depend implicitly on the minima. In RP, the amplitude of the ripples is explicitly specified and this leads to a set of non-linear (polynomial) equations with the position of both the minima and maxima as unknowns. An iterative algorithm is proposed to solve the equations and design examples will be presented. Two variations of the RP technique, which allow for the transition band sharpness to be explicitly specified, are also presented.

关键词： iterative methods Filtering methods in signal processing Interpolation and function approximation (numerical analysis) stopband minima iterative algorithm halfband filter design nonlinear equation zero-pinning technique orthonormal wavelet wavelet transforms Nonlinear and functional equations (numerical analysis) Filters and other networks ripple-pinning nonlinear equations Signal processing theory stopband maxima band-stop filters

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Group consensus algorithms based on preference relations

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INFORMATION SCIENCES 2011年第1期181卷 150-162页

作者： Xu, Zeshui Cai, Xiaoqiang Southeast Univ Sch Econ & Management Nanjing 210096 Jiangsu Peoples R China Chinese Univ Hong Kong Dept Syst Engn & Engn Management Shatin Hong Kong Peoples R China

In many group decision-making situations, decision makers' preferences for alternatives are expressed in preference relations (including fuzzy preference relations and multiplicative preference relations). An important step in the process of aggregating preference relations, is to determine the importance weight of each preference relation. In this paper, we develop a number of goal programming models and quadratic programming models based on the idea of maximizing group consensus. Our models can be used to derive the importance weights of fuzzy preference relations and multiplicative preference relations. We further develop iterative algorithms for reaching acceptable levels of consensus in group decision making based on fuzzy preference relations or multiplicative preference relations. Finally, we include an illustrative example. (C) 2010 Published by Elsevier Inc.

关键词： Group decision making Fuzzy preference relation Multiplicative preference relation Goal programming model Quadratic programming iterative algorithm

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