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iterative unbiased FIR state estimation: a review of algorithms

EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2013年第1期2013卷 1页

作者： Shmaliy, Yuriy S. Simon, Dan Univ Guanajuato Dept Elect Engn Salamanca 36855 Mexico Cleveland State Univ Dept Elect & Comp Engn Cleveland OH 44115 USA

In this paper, we develop in part and review various iterative unbiased finite impulse response (UFIR) algorithms (both direct and twoaEurostage) for the filtering, smoothing, and prediction of timeaEurovarying and timeaEuroinvariant discrete stateaEurospace models in white Gaussian noise environments. The distinctive property of UFIR algorithms is that noise statistics are completely ignored. Instead, an optimal window size is required for optimal performance. We show that the optimal window size can be determined via measurements with no reference. UFIR algorithms are computationally more demanding than Kalman filters, but this extra computational effort can be alleviated with parallel computing, and the extra memory that is required is not a problem for modern computers. Under realaEuroworld operating conditions with uncertainties, nonaEuroGaussian noise, and unknown noise statistics, the UFIR estimator generally demonstrates better robustness than the Kalman filter, even with suboptimal window size. In applications requiring large window size, the UFIR estimator is also superior to the best previously known optimal FIR estimators.

关键词： Unbiased FIR estimator Kalman filter iterative algorithm Filtering Smoothing Prediction

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Solution Characteristics of the Retarded-Time Equation for Transonic Rotating Sources

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AIAA JOURNAL 2013年第8期51卷 2035-2040页

作者： Tang, Hongtao Mao, Yijun Qi, Datong Xi An Jiao Tong Univ Dept Fluid Machinery & Engn Sch Energy & Power Engn Xian 710049 Shaanxi Peoples R China

The article presents a numerical solution for uniformly rotating transonic speed based on the retarded-time equation (RTE). It is assumed that the source rotating speed is less than the critical Mach number, and the local maximum and minimum points may be utilized to find all the roots of the RTE. The analytical root-bracketing approach is compared with the iterative procedure based on the acoustic pressure spectra produced by the RTE and exact frequency-domain methods.

关键词： Critical Mach Number Frequency Domain iterative algorithm Aeroacoustics Supersonic Speed Newton Raphson Method Doppler Effect Aircraft Propeller Helicopter Rotor Turbomachinery

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Robust minimum variance multiple-input multiple-output radar beamformer

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IET SIGNAL PROCESSING 2013年第9期7卷 854-862页

作者： Zhang, Wei Wang, Ju Wu, Siliang Beijing Inst Technol Dept Elect & Informat Beijing 100081 Peoples R China

A robust minimum variance (MV) beamforming approach is proposed for improving the robustness of multiple-input multiple-output (MIMO) radar against the mismatches of the steering vector and the finite sample effects. In contrast to existing robust MV beamformers (RMVBs), the proposed RMVB utilises a specific structured model of virtual steering vector (also named transmit-receive steering vector) of MIMO radar rather than the commonly used unstructured model in phased-array radar. The basic idea of the proposed RMVB is to estimate the desired transmit and receive steering vectors under two quadratic constraints. To solve this problem, an iterative algorithm is developed. Simulations are provided to confirm the effectiveness of the proposed method.

关键词： array signal processing iterative methods radar signal processing MIMO radar robust minimum variance MIMO radar beamformer robust MV beamforming approach multiple-input multiple-output radar finite sample effects virtual steering vector transmit-receive steering vector estimation phased-array radar quadratic constraint iterative algorithm

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Improving the efficiency of a mixed integer linear programming based approach for multi-class classification problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2013年第2期66卷 383-388页

作者： Maskooki, Alaleh FUM Dept Appl Math Mashhad Iran

Data classification is one of the fundamental issues in data mining and machine learning. A great deal of effort has been done for reducing the time required to learn a classification model. In this research, a new model and algorithm is proposed to improve the work of Xu and Papageorgiou (2009). Computational comparisons on real and simulated patterns with different characteristics (including dimension, high overlap or heterogeneity in the attributes) confirm that, the improved method considerably reduces the training time in comparison to the primary model, whereas it generally maintains the accuracy. Particularly, this speed-increase is significant in the case of high overlap. In addition, the rate of increase in training time of the proposed model is much less than that of the primary model, as the set-size or the number of overlapping samples is increased. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Data classification Mixed integer linear programming Hyper-boxes iterative algorithm

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Computation of Upper Bounds for the Solution of Continuous Algebraic Riccati Equations

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2013年第3期32卷 1477-1488页

作者： Zhang, Wei Su, Housheng Wang, Jia Shanghai Univ Engn Sci Lab Intelligent Control & Robot Shanghai 201620 Peoples R China Huazhong Univ Sci & Technol Dept Control Sci & Engn Key Lab Educ Minist Image Proc & Intelligent Control Wuhan 430074 Peoples R China

This paper is considered with the computation of upper bounds for the solution of continuous algebraic Riccati equations (CARE). A parameterized upper bound for the solution of CARE is proposed by utilizing some linear algebraic techniques. Based on this bound, more precise estimation can be achieved by means of carefully choosing the bound's parameters. iterative algorithm is also developed to obtain more sharper solution bounds. Comparing with some existing results in the literature, the proposed bounds are less restrictive and more effective. The effectiveness and advantages of the proposed approach are illustrated via a numerical example.

关键词： Continuous algebraic Riccati equation (CARE) Lyapunov equation Matrix bound iterative algorithm

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An accelerated RAMLA reconstruction algorithm for X-ray cone-beam CT

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INSIGHT 2013年第5期55卷 237-242页

作者： Zhao, Xing Hu, Jing-jing Yang, Tao Wang, Feng Capital Normal Univ Sch Math Sci Beijing 100048 Peoples R China Beijing Inst Technol Sch Software Beijing 100081 Peoples R China

iterative image reconstruction algorithms have many advantages over analytical image reconstruction algorithms in computed tomography. A widely applied iterative algorithm is OSEM (ordered subsets expectation maximisation), which has good reconstructed image quality and costs less in computation time. Compared with the conventional OSEM algorithm, another OS method RAMLA (row action maximum likelihood algorithm) can not only bring about significant acceleration in the iterative reconstruction, but also outperforms the OSEM in its convergence rate. In this paper, an accelerated RAMLA algorithm (ARAMLA) is proposed and applied to X-ray cone-beam CT image reconstruction. By increasing the step size of the correction factor, the ARAMLA algorithm can further speed up the RAMLA algorithm while still retaining its convergence properties. A graphics processing unit (GPU)-based implementation of the ARAMLA is also developed for greatly reducing the computation time per iteration. Experimental results show that to achieve the same image quality as in RAMLA, ARAMLA, with an accelerating factor of 2, requires only about half the number of iterations as RAMLA.

关键词： Computed tomography iterative algorithm cone-beam CT acceleration

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The coupled Sylvester-transpose matrix equations over generalized centro-symmetric matrices

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2013年第7期90卷 1546-1566页

作者： Beik, Fatemeh Panjeh Ali Salkuyeh, Davod Khojasteh Vali E Asr Univ Rafsanjan Dept Math Rafsanjan Iran Univ Guilan Fac Math Sci Rasht Iran

In this paper, we present an iterative algorithm for solving the following coupled Sylvester-transpose matrix equations Sigma(q)(j=1)(A(ij)X(j)B(ij) + (CijXjDij)-D-T) = F-i, i = 1, 2, ..., p, over the generalized centro-symmetric matrix group (X-1, X-2, ..., X-q). The solvability of the problem can be determined by the proposed algorithm, automatically. If the coupled Sylvester-transpose matrix equations are consistent over the generalized centro-symmetric matrices, then a generalized centro-symmetric solution group can be obtained within finite iterative steps for any initial generalized centro-symmetric matrix group in the exact arithmetic. Furthermore, it is shown that the least-norm generalized centro-symmetric solution group of the coupled Sylvester-transpose matrix equations can be computed by choosing an appropriate initial iterative matrix group. Moreover, the optimal approximate generalized centro-symmetric solution group to a given arbitrary matrix group (V-1, V-2, ..., V-q) can be derived by finding the least-norm generalized centro-symmetric solution group of a new coupled Sylvester-transpose matrix equations. Finally, some numerical results are given to illustrate the validity and practicability of the theoretical results established in this work.

关键词： coupled Sylvester-transpose matrix equations iterative algorithm generalized centro-symmetric matrix 15A24 65F10

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Convergence of fixed-point iteration for the identification of Hammerstein and Wiener systems

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 2013年第13期23卷 1510-1523页

作者： Li, Guoqi Wen, Changyun ASTAR Data Storage Inst Opt Mat & Syst OMS Div Singapore 117608 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

Convergence property of the iterative algorithm for Hammerstein or Wiener systems is generally hard to establish because of the existence the unmeasurable internal variables in such systems. In this paper, a fixed-point iteration is introduced to identifying both Hammerstein and Wiener systems with a unified algorithm. This newly proposed estimation algorithm gives consistent estimates under arbitrary nonzero initial conditions. In addition, the errors of the estimates are established as functions of the noise variance, and thus how the noise affects the quality of parameter estimates for a finite number of data points is made clear. Copyright (c) 2012 John Wiley & Sons, Ltd.

关键词： nonlinear system identification fixed-point iteration Hammerstein systems Wiener systems iterative algorithm convergence

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Spacecraft Attitude Tracking with Guaranteed Performance Bounds

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2013年第4期36卷 1214-1221页

作者： de Ruiter, Anton H. J. Ryerson Univ Toronto ON M5B 2K3 Canada

A study was conducted to investigate spacecraft attitude tracking with guaranteed performance bounds. Guaranteed analytical performance bounds were obtained in the presence of model uncertainties and measurement errors. The bounds were useful for attitude-control system designers to assist in gain selection given steady-state performance specifications, reducing the need for time-consuming Monte Carlo analyses. It was shown that if the filtered error was ultimately upper bounded with known bound, then the attitude and body-rate errors were ultimately upper bounded. Bounds on the steady-state tracking errors were derived using this result along with sequential Lyapunov-type analyses, when bounded model uncertainties and measurement errors were present.

关键词： Spacecraft Attitude Quaternions Attitude Tracking Attitude Control System Closed Loop System Control System Design iterative algorithm Feedback Control

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Gradient-based parameter estimation for input nonlinear systems with ARMA noises based on the auxiliary model

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NONLINEAR DYNAMICS 2013年第4期72卷 865-871页

作者： Chen, Jing Zhang, Yan Ding, Ruifeng Jiangnan Univ Key Lab Adv Proc Control Light Ind Minist Educ Wuxi 214122 Peoples R China Wuxi Profess Coll Sci & Technol Wuxi 214028 Peoples R China Wuxi Inst Technol Wuxi 214121 Peoples R China

This paper presents a gradient-based iterative identification algorithm and an auxiliary-model-based multi-innovation generalized extended stochastic gradient algorithm for input nonlinear systems with autoregressive moving average (ARMA) noises, i.e., the input nonlinear Box-Jenkins (IN-BJ) systems. The estimation errors given by the gradient-based iterative algorithm are smaller than the generalized extended stochastic gradient algorithm under same data lengths. A simulation example is provided.

关键词： Parameter estimation Stochastic gradient iterative algorithm Auxiliary model Recursive identification Nonlinear system

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