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Chinese Intelligent Systems Conference (CISC)

作者： Li, Linwei Ren, Xuemei Zhao, Wei Wang, Minlin Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China

ISBN: (纸本)9789811023354;9789811023347

In this paper, two-stage recursive least squares algorithm (TS-RLS) is investigated for parameter identification of cascade systems with dead zone. In order to estimate the slopes and endpoints of the dead zone, switching functions are presented to reconstruct the expression of dead zone. All the parameters of linear subsystems and dead zone are separated by using the key term separation principle, which is applied to convert the cascade systems into a quasilinear model. The proposed identification algorithm not only estimates all the parameters of the cascade systems, but also reduces the computation cost of identification process. The result of the simulation illustrates the flexibility and efficiency of proposed identification algorithm.

关键词： Parameter identification Dead zone two-stage algorithm Cascade systems

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A New two-step algorithm for Spotlight Synthetic Aperture Radar Imaging 20

A New Two-step Algorithm for Spotlight Synthetic Aperture Ra...

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Conference on Radar Sensor Technology XX

作者： Sun, Ligang Zhang, Lei Wang, Guanyong Hu, Mengqi Qiao, Zhijun G. Univ Texas Rio Grande Valley Sch Math & Stat Sci Edinburg TX 78539 USA Xidian Univ Xian 710071 Peoples R China

ISBN: (纸本)9781510600706

In this paper, we designed a new two-stage algorithm to formulate accurately the focusing image with the highly squinted synthetic aperture radar. First of all is the general model of the squinted synthetic aperture radar (SAR) focusing a fixed area. After the echo data collection, the first stage of the algorithm is to establish the coarse image by performing the conventional range cell migration correction and azimuth matched filtering. In the second stage, the azimuth-variant was corrected and the motion compensation was carried to achieve a better image. A simulation experiment was given in the end.

关键词： Synthetic Aperture Radar spolight SAR model motion compensation (MOCO) two-stage algorithm

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Switching Time Optimization for Discontinuous Switched Systems

Switching Time Optimization for Discontinuous Switched Syste...

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European Control Conference (ECC)

作者： Schori, Markus Boehme, Thomas J. Jeinsch, Torsten Lampe, Bernhard IAV Automot Engn Dept Gasoline Engine Syst D-38518 Gifhorn Germany Univ Rostock Inst Automat D-18119 Rostock Germany

ISBN: (纸本)9783952426937

In this paper, an algorithm for switching time optimization for switched systems that exhibit discontinuities in the state trajectory on a switching is proposed. A derivative of the cost function with respect to the switching time is derived using a dynamic programming argumentation. Based on this derivative, a two-stage algorithm is described that alternates between solving an optimal control problem with fixed switching sequence and improving the switching times.

关键词： dynamic programming optimal control sampled data systems switching systems (control) cost function discontinuous switched systems dynamic programming argumentation fixed switching sequence optimal control problem state trajectory switching time optimization two-stage algorithm Cost function Optimal control Switched systems Switches Trajectory

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Computational Complexity Reduction for Functional Connectivity Estimation in Large Scale Neural Network 22nd

Computational Complexity Reduction for Functional Connectivi...

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22nd International Conference on Neural Information Processing (ICONIP)

作者： Baek, JeongHun Oba, Shigeyuki Yoshimoto, Junichiro Doya, Kenji Ishii, Shin Kyoto Univ Grad Sch Informat Yoshidahonmachi 36-1 Kyoto Japan Grad Univ Okinawa Inst Sci & Technol Neural Computat Unit Okinawa 9040495 Japan Nara Inst Sci & Technol Grad Sch Informat Sci Nara 6300101 Japan

ISBN: (纸本)9783319265551;9783319265544

Identification of functional connectivity between neurons is an important issue in computational neuroscience. Recently, the number of simultaneously recorded neurons is increasing, and computational complexity to estimate functional connectivity is exploding. In this study, we propose a two-stage algorithm to estimate spike response functions between neurons in a large scale network. We applied the proposed algorithm to various scales of neural networks and showed that the computational complexity is reduced without sacrificing estimation accuracy.

关键词： Computational complexity reduction Functional connectivity two-stage algorithm Large scale networks

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two-stage Recursive Least Squares Method for Modeling Power Signals 4

Two-stage Recursive Least Squares Method for Modeling Power ...

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The Fourth International Conference On Control, Automation and Information Sciences

作者： Li, Xiangli Zhou, Lincheng Zhu, Peiyi Changshu Inst Technol Sch Elect & Automat Engn Changshu Peoples R China

ISBN: (纸本)9781479998920

This paper studies two-stage recursive least squares identification problems for power signals by the decomposition technique. The basic idea is to decompose a power signal model into two submodels and then to identify the parameters of each submodel, respectively. Compared with the recursive least squares algorithm, the dimensions of the involved covariance matrices in each submodel become small and thus the proposed algorithm has a high computational efficiency. Finally, the simulation results indicate that the proposed algorithm is effective.

关键词： least squares parameter estimation two-stage algorithm decomposition technique power signals

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Joint estimation of the fractional differentiation orders and the unknown input for linear fractional non-commensurate system

Joint estimation of the fractional differentiation orders an...

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IEEE Conference on Control and Applications (CCA)

作者： Belkhatir, Zehor Laleg-Kirati, Taous-Meriem King Abdullah Univ Sci & Technol Comp Elect & Math Sci & Engn Div Thuwal Saudi Arabia

ISBN: (纸本)9781479977871

This paper deals with the joint estimation of the unknown input and the fractional differentiation orders of a linear fractional order system. A two-stage algorithm combining the modulating functions with a first-order Newton method is applied to solve this estimation problem. First, the modulating functions approach is used to estimate the unknown input for a given fractional differentiation orders. Then, the method is combined with a first-order Newton technique to identify the fractional orders jointly with the input. To show the efficiency of the proposed method, numerical examples illustrating the estimation of the neural activity, considered as input of a fractional model of the neurovascular coupling, along with the fractional differentiation orders are presented in both noise-free and noisy cases.

关键词： Newton method differentiation first-order Newton method fractional differentiation order estimation linear fractional noncommensurate system linear fractional order system modulating function approach neural activity estimation neurovascular coupling two-stage algorithm unknown input estimation Estimation error Joints Mathematical model Noise measurement Polynomials Newton method joint estimation Noise measurement Estimation error differentiation Differentiation Polynomial Joints Joints Mathematical Model Neurovascular Coupling Individualized Instruction

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A Novel two-stage algorithm of Fuzzy C-Means Clustering

A Novel Two-stage Algorithm of Fuzzy C-Means Clustering

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2010 International Conference on Computer,Mechatronics, Control and Electronic Engineering (CMCE 2010)

作者： Shanhong ZHENG Computer Science and Technology College JiLin University Computer Science and Engineering College ChangChun University of Technology ChangChun,China Chunguang ZHOU Computer Science and Technology College JiLin University ChangChun,China Guixia LIU Computer Science and Technology College JiLin University ChangChun,China Wanlong LI Computer Science and Engineering College ChangChun University of Technology ChangChun,China

Fuzzy C-Means is one of the clustering algorithms based on optimizing an objective *** selection of the initial parameters of the number and the initial cluster centers play an important influence in the performance of the *** paper proposes a new FCM clustering algorithm with two *** proposed algorithm not only resolves the problem of the initial choice of the cluster center effectively,but also decreases the time when clustering large volume of *** computer simulation results show the effectivity and the superiority of the new algorithm.

关键词： Fuzzy C-Means clustering algorithm initial cluster center two-stage algorithm

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A Novel two-stage algorithm of Fuzzy C-Means Clustering

A Novel Two-stage Algorithm of Fuzzy C-Means Clustering

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2010 International Conference on Computer,Mechatronics,Control and Electronic Engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

作者： Shanhong ZHENG Chunguang ZHOU Guixia LIU Wanlong LI Computer Science and Technology College JiLin University Computer Science and Engineering College Ch Computer Science and Technology College JiLin University ChangChun China Computer Science and Engineering College ChangChun University of Technology ChangChun China

Fuzzy C-Means is one of the clustering algorithms based on optimizing an objective function. The selection of the initial parameters of the number and the initial cluster centers play an important influence in the performance of the FCM. This paper proposes a new FCM clustering algorithm with two stages. The proposed algorithm not only resolves the problem of the initial choice of the cluster center effectively, but also decreases the time when clustering large volume of data. The computer simulation results show the effectivity and the superiority of the new algorithm.

关键词： Fuzzy C-Means clustering algorithm initial cluster center two-stage algorithm

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Optimal spectrum assignment for cognitive radio sensor networks under coverage constraint

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IET COMMUNICATIONS 2014年第18期8卷 3318-3325页

作者： Eletreby, Rashad M. Elsayed, Hany M. Khairy, Mohamed M. Cairo Univ Fac Engn Dept Elect & Elect Commun Engn Cairo Egypt

Cognitive radios emerged as a solution to spectrum scarcity problem. The integration of cognitive radios and wireless sensor networks enables a new paradigm of communication, in which the sensor nodes can avoid heavily-crowded transmission bands by tuning their transmission parameters to less-crowded bands. The authors consider the problem of spectrum assignment for cognitive radio sensor network (CRSN) under coverage, interference, minimum data rate and power budget constraints. A mixed-integer non-linear programming problem formulation that addresses optimal power allocation, channel selection and node scheduling is presented. Following a practical assumption, that any CRSN node can only access one channel for its transmission with the CRSN base station, the problem is transformed to a binary linear programming (BLP) problem. Using the relaxation techniques, the problem is transformed to a linear programming problem that is solvable in polynomial time, and has the same optimal solution of the BLP problem. Hence, the minimum power algorithm that achieves the optimal solution of our problem is proposed. To further reduce the complexity of the solution, three heuristic lower-complexity algorithms are proposed to solve the problem: random, greedy and two-stage (decoupled) algorithms.

关键词： radio spectrum management cognitive radio radio networks wireless sensor networks radiofrequency interference nonlinear programming integer programming scheduling wireless channels linear programming polynomials greedy algorithms random processes optimal spectrum assignment cognitive radio sensor network spectrum scarcity problem wireless sensor network heavily-crowded transmission band avoidance CRSN interference power budget constraint minimum data rate constraint mixed-integer nonlinear programming problem optimal power allocation channel selection node scheduling base station binary linear programming problem BLP problem relaxation technique polynomial time minimum power algorithm heuristic lower-complexity algorithm random algorithm greedy algorithm two-stage algorithm decoupled algorithm

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Revisiting Hammerstein system identification through the two-stage algorithm for bilinear parameter estimation

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AUTOMATICA 2009年第11期45卷 2627-2633页

作者： Wang, Jiandong Zhang, Qinghua Ljung, Lennart INRIA F-35042 Rennes France Peking Univ Coll Engn Beijing 100871 Peoples R China Linkoping Univ Dept Elect Engn SE-58183 Linkoping Sweden

The two-stage algorithm (TSA) has been extensively used and adapted for the identification of Hammerstein systems. It is essentially based on a particular formulation of Hammerstein systems in the form of bilinearly parameterized linear regressions. This paper has been motivated by a somewhat contradictory fact: though the optimality of the TSA has been established by Bai in 1998 only in the case of some special weighting matrices, the unweighted TSA is usually used in practice. It is shown in this paper that the unweighted TSA indeed gives the optimal solution of the weighted nonlinear least squares problem formulated with a particular weighting matrix. This provides a theoretical justification of the unweighted TSA, and also leads to a generalization of the obtained result to the case of colored noise with noise whitening. Numerical examples of identification of Hammerstein systems are presented to validate the theoretical analysis. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Nonlinear system identification Hammerstein system two-stage algorithm Bilinear equation

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