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Novel algorithm for communication signal blind separation-EASIBSA algorithm

Wuhan Ligong Daxue Xuebao/Journal of Wuhan University of technology 2008年第1期30卷 91-94页

作者： Fu, Wei-Hong Yang, Xiao-Niu Liu, Nai-An Zeng, Xing-Wen State Key Lab. of Integrated Service Networks Xidian University Xi'an 710071 China National Laboratory of Information Control Technology for Communication System Jiangnan Electronic Communications Research Institute Jiaxing 314033 China

Aim at the problem of the communication signal blind source separation, a novel blind separation algorithm based on step size adaptation (EASIBSA) to increase the convergence rate of the separation algorithm was present by using the idea of parameter adaptation optimization, which was based on Equivariant Adaptive Separation via Independent (EASI) algorithm. This algorithm related the learning rate with the object function and adapted it by using the stochastic gradient method, which avoided the selection of optimum learning rate and speed up the convergence rate. Simulation results showed that improved algorithm could increase the convergence rate of separation algorithm by two times without affecting the separation capability.

关键词： Blind source separation Convergence rate Digital communication Parameter adaptation

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Improved IPR method based on signal subspace

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Wuhan Ligong Daxue Xuebao/Journal of Wuhan University of technology 2008年第11期30卷 158-161页

作者： Ji, Da-Zhuang Zhan, Yi Zuo, Ji-Zhang Wang, Guo-Hong Li, Sheng-Jun School of Engineering Air Force Engineering University Xi'an 710038 China National Laboratory of Information Control Technology for Communication System Jiaxing 314033 China Jiangnan Electronic Communication Research Institute Jiaxing 314033 China Radar and Electronic Warfare Institute EAAF Beijing 100085 China

In this paper, we consider the problem of DOA estimation using the improved polynomial rooting (IPR) method. When the IPR method is used in the cases that there are few sources with same frequency, the matrix composed of noise eigenvectors is processed complexly. So we construct the matrix for computing the coefficient of polynomial with signal subspace. This method is effective in theory and computer simulation. It reduces the complexity of IPR method. Further more, its performance is better than MUSIC method.

关键词： DOA estimation IPR method MUSIC method Signal subspace

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The Monte Carlo framework for adaptive HR filter & ARMA parameters estimation

The Monte Carlo framework for adaptive HR filter & ARMA para...

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IET Conference on Wireless, Mobile and Sensor Networks 2007, CCWMSN'07

作者： Wang, Li-Xin Xiang, Wei Zhang, Jing-Yuan Institute of Electronic and Information System Hangzhou Dianzi University Hangzhou 310018 China National Laboratory of Information Control Technology for Communication System Jiaxing 314001 China

ISBN: (纸本)9780863418365

Adaptive filter is widely used in many cases and usually formed in FIR structure. However, in multi-path wireless channel equalization, the channel can be presented as full zero-point model, and the difficulty will be encountered for equalization using adaptive FIR filter. In this situation, the channel can be compensated with satisfy characteristics by using adaptive IIR filter and obtain better performance than FIR. Unfortunately, the general IIR algorithm is difficult to perform filtering with robust and downright. In another signal processing field, such as spectrum estimation and system identification, the classical approach is to model the signal (or system) as ARMA process, i.e., a signal can be regarded as an output of a filter with some zero-pole in system function excited by white noise. Compared with AR model, in ARMA process, although there are some faulty algorithms before which bring troubles in high complexity and uncertain result, but the mature technology is absence as yet. Similarly, ARMA model can also be equivalent with a IIR filter, that's to adjust the parameters to enable the filter's output close with a reference signal. This paper proposes a new framework for adaptive IIR filter and ARMA parameter estimation based Monte Carlo particle filter, and the agility is demonstrated by computer simulation. The degeneracy phenomena will not occur in filtering. Simulation results indicated that the new method is feasible.

关键词： Parameter estimation

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Step-size optimization EASI algorithm for blind source separation

Step-size optimization EASI algorithm for blind source separ...

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2007 International Conference on Computational Intelligence and Security, CIS'07

作者： Weihong, Fu Xiaoniu, Yang Naian, Liu State Key Lab. of Integrated Service Networks Xidian University Xi'an 710071 China National Laboratory of Information Control Technology for Communication System Jiaxing Zhejiang 31403 China

ISBN: (纸本)0769530729

Aiming at the problem of blind source separation of the communication signals, we propose a step size optimization equivariant adaptive source separation via independence (SO-EASI) algorithm basing on the EASI block based algorithm. This algorithm adjusts the step-size by the steepest descent method and thereby greatly increases its convergence speed whatever value the step-size is initialized. Simulation results show that SO-EASI algorithm can effectively blindly separate the communication signals and these results also support the expected improvement in convergence speed of the approach. © 2007 IEEE.

关键词： Blind source separation

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The Monte Carlo framework for adaptive IIR filter & ARMA parameters estimation

The Monte Carlo framework for adaptive IIR filter & ARMA par...

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2007 IET Conference on Wireless, Mobile and Sensor Networks (CCWMSN07)

作者： Li-xin Wang Wei Xiang Jing-yuan Zhang Institute of electronic &information system Hangzhou Dianzi University Hangzhou China National Laboratory of Information Control Technology for Communication System Jiaxing China

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Research on identifiability of equivalent motor in composite load model

Research on identifiability of equivalent motor in composite...

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2007 IEEE Lausanne POWERTECH

作者： Ma, Jin Han, Dong He, Renmu Dong, Zhaoyang Hill, David J. IEEE Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control Ministry of Education North China Electric Power University 102206 Beijing China School of Information Technology and the Electrical Engineering University of Queensland St. Lucia QLD 4072 Australia Department of Information Engineering Australian National University

ISBN: (纸本)9781424421909

Load modeling is very important for power system dynamic analysis and control. The composite load model widely applied recently in the power system operation centre consists of the static load and the equivalent motor. Current practices in measurement-based load modeling identify all the parameters in this composite load model. However, it is not clear whether all these parameters could be identified from the measurements. This paper investigates the identifiability of the equivalent motor parameters in the composite load model. Trajectory sensitivity approach is applied first to find the motor parameters that have great effects on the measured active as well as reactive load dynamics. The analysis results show that the motor outputs have various sensitivities with respect to the parameters. Since the voltage disturbance, the active load and the reactive load dynamics are applied to identify the motor parameters, those parameters affecting the measurements to a great extent are observable, thus identifiable from the measurements;while those that have little effects on the motor outputs are unobservable from the measurements and consequently unidentifiable. The case studies verify the identifiability of the motor parameters. ©2007 IEEE.

关键词： Parameter estimation

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Concurrent Modified Square Contour Algorithm and Soft Decision-Directed Scheme for Blind Equalization

Concurrent Modified Square Contour Algorithm and Soft Decisi...

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Shunlan Liu Mingzeng Dai Caiyi Lou School of Communication Engineering Hangzhou Dianzi University Hangzhou Zhejiang China Control Technology for Commutation System National Laboratory for Information Science and Technology Jiaxing Zhejiang China

A new blind equalization scheme is proposed based on concurrent modified square contour algorithm (MSCA) and a novel soft decision-directed (SDD) adaptation. This proposed blind equalization scheme (MSCA+SDD) may be viewed as operating a MSCA equalizer and a SDD equalizer concurrently. The MSCA term provides good steady- state equalization performance and global convergence, moving the equalizer weight vector on the correct direction; after the equalizer enters the fine local convergence region, the SDD term helps to accelerate convergence. The performance is measured for realistic microwave channel models and the simulation results demonstrate that both the MSCA+SDD and the MSCA have the same steady-state equalization performance, but the former has a faster convergence speed.

关键词： Blind equalizers Decision feedback equalizers Convergence Steady-state Constellation diagram Acceleration Clustering algorithms Laboratories communication system control control systems

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Measurement-based load modeling using genetic algorithms

Measurement-based load modeling using genetic algorithms

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2007 IEEE Congress on Evolutionary Computation, CEC 2007

作者： Ma, Jin Dong, Zhao-Yang He, Ren-Mu Hill, David J. IEEE Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control North China Electric Power University Ministry of Education 102206 Beijing China School of Information Technology and Electrical Engineering University of Queensland St. Lucia QLD 4072 Australia Department of Information Engineering Australian National University Australia

ISBN: (纸本)1424413400

Load modeling is very important to power system operation and control. Measurement-based load modeling has been widely practiced in recent years. Mathematically, measurement-based load modeling problem are closely related to the parameter identification area. Consequently, an efficient optimization method is needed to derive the load model parameters based on the feedback of estimation errors between the measurements and model outputs. This paper reports our work on applying genetic algorithms on measurement-based load modeling research. Due to its robustness to the initial guesses on the load model parameters, genetic algorithms are very suitable for load model parameter identification. Two cases including both the real measurement in a power station and the digital simulation are studied in the paper. For comparison purpose, the classical nonlinear least square estimation method is also applied to find the load model parameters. The simulated outputs from the load model confirm the efficiency of genetic algorithms in measurement-based load modeling analysis. Future work will focus on fastening the converging speed of the genetic algorithms, and/or utilizing more efficient evolutionary computation methods. © 2007 IEEE.

关键词： Electric load management

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Research on Identifiability of Equivalent Motor in Composite Load Model

Research on Identifiability of Equivalent Motor in Composite...

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Power Tech Conference

作者： Ma Jin Han Dong He Renmu Dong Zhaoyang David J. Hill Key Laboratory of Power System Protection and Dynamic Security Monitoring and Control of Ministry of Education North China Electric Power University Beijing China School of Information Technology and the Electrical Engineering University of Queensland Saint Lucia QLD Australia Department of Information Engineering Australian National University Australia

Load modeling is very important for power system dynamic analysis and control. The composite load model widely applied recently in the power system operation centre consists of the static load and the equivalent motor. Current practices in measurement-based load modeling identify all the parameters in this composite load model. However, it is not clear whether all these parameters could be identified from the measurements. This paper investigates the identifiability of the equivalent motor parameters in the composite load model. Trajectory sensitivity approach is applied first to find the motor parameters that have great effects on the measured active as well as reactive load dynamics. The analysis results show that the motor outputs have various sensitivities with respect to the parameters. Since the voltage disturbance, the active load and the reactive load dynamics are applied to identify the motor parameters, those parameters affecting the measurements to a great extent are observable, thus identifiable from the measurements; while those that have little effects on the motor outputs are unobservable from the measurements and consequently unidentifiable. The case studies verify the identifiability of the motor parameters.

关键词： Load modeling Power system modeling Power system dynamics Power system simulation Power system stability Power system analysis computing Power system measurements Voltage Power system control Power systems

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Measurement-based Load Modeling using Genetic Algorithms

Measurement-based Load Modeling using Genetic Algorithms

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Congress on Evolutionary Computation

作者： Jin Ma Ren-mu He Zhao-yang Dong David J. Hill Key Laboratory of Power System Protection and Dynamic Secutitu Monitoring and Control of Ministy of Education North China Electric Power University Beijing China The School of Information Technology and Electrical Engineering University of Queensland QLD Australia The Department of Infotmation Engineering Australian National University Australia

关键词： Load modeling Genetic algorithms Power system modeling Parameter estimation Power system measurements Power system control Power systems control system synthesis Area measurement Optimization methods

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