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International Joint Conference on Neural Networks (IJCNN)

作者： Chen, Zhitang Chan, Laiwan Chinese Univ Hong Kong Dept Comp Sci & Engn Shatin Hong Kong Peoples R China

ISBN: (纸本)9781424496365

Permutation indeterminacy and scaling ambiguity occur in ICA and they are particularly problematic in time-frequency domain separation of convolutive mixtures. The quality of separation is severely degraded if these two problems are not well addressed. In this paper, we propose new approaches to solve the permutation indeterminacy and scaling ambiguity in the separation of convolutive mixture in frequency domain. We first apply Short Time Fourier Transform to the observed signals in order to transform the convolutive mixing in time domain to instantaneous mixing in time-frequency domain. A fixed-point algorithm with test of saddle point is adopted to derive the separated components in each frequency bin. To solve the permutation problem, we propose a new matching algorithm for this purpose. First we use discrete Haar Wavelet Transform to extract the feature vectors from the magnitude waveforms of the separated components and use Singular Value Decomposition to achieve dimension reduction. The permutation problem is solved by clustering the feature vectors using the new matching algorithm which is a combination of basic K-means and Hungarian algorithm. To solve the scaling ambiguity problem, we treat it as an overcomplete problem and realize it by maximizing the posterior of the scaling factor. Finally, experiments are conducted using benchmark data to present the effectiveness and performance of our proposed algorithms.

关键词： Clustering algorithms Feature extraction Fourier transforms Haar transforms Hungarian algorithm K-means algorithm Time domain analysis Time frequency analysis Wavelet transforms blind source separation blind source separation convolution convolutive mixtures dimension reduction discrete Haar wavelet transform feature extraction feature vector extraction fixed-point algorithm independent component analysis independent component analysis matching algorithm pattern matching permutation indeterminacy scaling ambiguity problem short time Fourier transform singular value decomposition singular value decomposition time-frequency analysis time-frequency domain separation wavelet transforms

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Signal Separation for Vibration Signals in the Gas Turbine Based on Independent Component Analysis

Signal Separation for Vibration Signals in the Gas Turbine B...

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2011 International Conference on Management Science and Intelligent Control(ICMSIC 2011)

作者： Qiuyan Wang, jie Ma college of Automation Beijing Information Science & Technology University Beijing 100192, China Xiaoli Xu Key Laboratory of Modern Measurement & Control Ministry of Education Beijing Information Science & Technology University Beijing 100192, China

Multivariate statistical process control (MSPC) is based on the assumption that the industrial process data must be subject to normal distribution. Under the normal operation condition, the industrial process data can not be satisfied and the monitoring signals collected are mostly the mixed-signals. The method on how to separate the each vibration signal from the mixed-signals was pro-posed in this paper. Independent component analysis (ICA) is a new statistical method that generated in recent years, which can over-come the dependence of data distribution. The fixed-point algo-rithm of negentropy based on Independent Component Analysis was researched in this article. At last, the simulation was made on the normal signals and the vibration signals of gas turbine in Yan-shan Petrochemical Gas plant of Beijing, the results show that this method is effective and useful.

关键词： Independent component analysis (ICA) fixed-point algorithm vibration signal

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fixed-point CONTINUATION APPLIED TO COMPRESSED SENSING:IMPLEMENTATION AND NUMERICAL EXPERIMENTS

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Journal of Computational Mathematics 2010年第2期28卷 170-194页

作者： Elaine T.Hale Department of Computational and Applied Mathematics Rice University

fixed-point continuation （FPC） is an approach, based on operator-splitting and continuation, for solving minimization problems with l1-regularization：min ｜｜x｜｜1＋uf（x）.We investigate the application of this algorithm to compressed sensing signal recovery, in which f（x） = 1/2｜｜Ax-b｜｜2M,A∈m×n and m≤n. In particular, we extend the original algorithm to obtain better practical results, derive appropriate choices for M and u under a given measurement model, and present numerical results for a variety of compressed sensing problems. The numerical results show that the performance of our algorithm compares favorably with that of several recently proposed algorithms.

关键词： l1 regularization fixed-point algorithm Continuation Compressed sensing,Numerical experiments.

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Complexity Pursuit for Unifying Model

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NEURAL PROCESSING LETTERS 2010年第1期31卷 17-24页

作者： Yang, Yumin Anshan Normal Univ Dept Math Anshan 114001 Peoples R China

Complexity pursuit is an extension of projection pursuit to time series data and the method is closely related to blind separation of time-dependent source signals and independent component analysis. The goal is to find projections of time series that have interesting structure, defined using criteria related to Kolmogoroff complexity or coding length. In this paper, we first derive a simple approximation of coding length for unifying model that takes into account nongaussianity of sources, their autocorrelations and their smoothly changing nonstationary variances. Next, a fixed-point algorithm is proposed by using approximate Newton method. Finally, simulations verify the fixed-point algorithm converges faster than the existing gradient algorithm and it is more simple to implement due to it does not need any learning rate.

关键词： Independent component analysis Blind source separation Complexity pursuit Kolmogoroff complexity fixed-point algorithm

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Energy-Efficient Multi-Carrier Link Adaptation with Sum Rate-Dependent Circuit Power

Energy-Efficient Multi-Carrier Link Adaptation with Sum Rate...

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IEEE Global Telecommunications Conference (GLOBECOM 2010)

作者： Isheden, Christian Fettweis, Gerhard P. Tech Univ Dresden Vodafone Chair Mobile Commun Syst D-01069 Dresden Germany

ISBN: (纸本)9781424456383

Energy-efficient link adaptation is studied for transmission on a frequency-selective parallel AWGN channel. The total power dissipation model includes a circuit power that varies with the sum rate and a power amplifier efficiency that varies with the bandwidth used. The mathematical analysis provides insight into how the subcarrier rates should be chosen for optimal energy efficiency and suggests a simple fixed-point algorithm that finds the solution in few iterations. Moreover, ways of improving the energy efficiency are discussed based on the dependence on bandwidth and distance between transmitter and receiver.

关键词： AWGN channels energy-efficient multicarrier link adaptation fixed-point algorithm frequency-selective parallel AWGN channel mathematical analysis mathematical analysis mobile communication mobile communication devices power amplifier efficiency power ampl

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Design of Feedback Linearization Control and Reconfigurable Control Allocation with Application to a Quadrotor UAV

Design of Feedback Linearization Control and Reconfigurable ...

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Conference on Control and Fault-Tolerant Systems (SysTol)

作者： Zhou, Qing-Li Zhang, Youmin Rabbath, Camille-Alain Theilliol, Didier Concordia Univ Mech & Ind Engn Montreal PQ H3G 2W1 Canada Concordia Univ Dept Mech & Ind Engn Diag Flight Control & Simulat Lab Montreal PQ H3G 2W1 Canada Def Res & Dev Canada Valcartier PQ G3J 1X5 Canada Ctr Rech Automat Nancy CNRS UMR 7039 Nancy France

ISBN: (纸本)9781424481545

Based on the developed nonlinear dynamic equations of a quadrotor (named as Qball-X4) UAV (Unmanned Aerial Vehicle), attitude and trajectory tracking control designs based on an inner/outer loop control structure has been proposed in this paper. Feedback linearization is designed to control the attitude stability in inner loop, traditional PID is designed to follow trajectory in accordance with pre-planned paths based on the Qball-X4 nonlinear model. For taking care of faults occurred in the UAV during the flight, reconfigurable control allocation is implemented together with the above controllers. Performance of constrained optimization algorithm for reconfigurable control allocation design - fixed-point (Fix) algorithm with applications to Qball-X4 is evaluated under different partial-loss fault cases. Various simulation results have been provided to demonstrate the validity of the fault tolerant control system design and the effectiveness of the reconfigurable control allocation design in trajectory tracking control.

关键词： Qball-X4 nonlinear model aerospace robotics attitude control attitude control constrained optimization algorithm feedback feedback linearization control fixed-point algorithm mobile robots nonlinear control systems optimisation position control quadrotor UAV reconfigurable control allocation remotely operated vehicles trajectory tracking control unmanned aerial vehicles

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Improved algorithm for Independent Component Analysis

Improved Algorithm for Independent Component Analysis

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The 2010 2nd International Conference on Future Computer and Communication(第二届未来计算机与通信国际会议 ICFCC 2010)

作者： Ju Ce Yu Yang Yu Peng Department of Information Science and Engineering Northeast University Shenyang Liaoning Province China

ISBN: (纸本)9781424458219;9781424458240

Firstly, this paper introduces the basic theory of Independent Component Analysis (ICA) and the FastICA algorithm. In order to increase the algorithm convergence rate and reduce the running time, the paper amends the Newton's iteration method and gives an improved algorithm of independent component analysis-the Newton's iteration method with fifthorder convergence. The simulation result of the image signal separation shows that the improved algorithm have the same separate effect as conventional FastICA algorithm and can reduce the times of iterations and the running time significantly. Furthermore, the improved algorithm can also increase the convergence rate and operation efficiency.

关键词： Independent component analysis fixed-point algorithm Newton's iteration method Negentropy

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Semi-blind source extraction algorithm for fetal electrocardiogram based on generalized autocorrelations and reference signals

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2009年第1期223卷 409-420页

作者： Zhang, Hongjuan Shi, Zhenwei Guo, Chonghui Feng, Enmin Dalian Univ Technol Inst Syst Engn Dalian 116024 Peoples R China Dalian Univ Technol Dept Appl Math Dalian 116024 Peoples R China Beijing Univ Aeronaut & Astronaut Sch Astronaut Image Proc Ctr Beijing 100083 Peoples R China

Blind source extraction (BSE) has become one of the processing methods in the field of signal processing and analysis, which only desires to extract "interesting" source signals with specific stochastic property or features so as to save lots of computing time and resources. This paper addresses BSE problem, in which desired source signals have some available reference signals. Based oil this prior information, we develop an objective function for extraction of temporally correlated sources. Maximizing this objective function, a semi-blind source extraction fixed-point algorithm is proposed. Simulations on artificial electrocardiograph (ECG) signals and the real-world ECG data demonstrate the better performance of the new algorithm. Moreover, comparisons with existing algorithms further indicate the validity of our new algorithm, and also show its robustness to the estimated error of time delay. (c) 2008 Elsevier B.V All rights reserved.

关键词： Independent component analysis Semi-blind source extraction Constrained optimization Generalized autocorrelation fixed-point algorithm

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Quantitative Analyses on the Finite Precision Effect of Computerized Logistic Map

Quantitative Analyses on the Finite Precision Effect of Comp...

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International Conference on Wireless Communications and Signal Processing

作者： Zhang, Bo Wang, Guangyi Han, Chunyan Hangzhou Dianzi Univ Sch Elect Informat Hangzhou Zhejiang Peoples R China Binzhou Univ Dept Phys & Elect Sci Binzhou Shandong Peoples R China

ISBN: (纸本)9781424448562

The aperiodic chaotic signals turn out to be periodic signals in the computerizing realization due to the finite precision effect. Currently there doesn't exist quantitative analyses in this field. Inspired by the AD/DA method this paper simulates the fixed-point algorithm in floating-point environment, and then employs curve-fitting method to get the quantitative relation between the maximum cycle of the chaotic orbit and the digital precision in computerizing chaotic logistic map.

关键词： chaos Logistic map finite precision effect fixed-point algorithm

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fixed-point blind source separation algorithm based on ICA

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Frontiers of Electrical and Electronic Engineering in China 2008年第3期3卷 343-346页

作者： Hongyan LI Jianfen MA Deng’ao LI Huakui WANG College of Information Engineering Taiyuan University of TechnologyTaiyuan 030024China

This paper introduces the fixed-point learning algorithm based on independent component analysis(ICA);the model and process of this algorithm and simulation results are *** was adopted as the estimation rule of *** results of the experiment show that compared with the traditional ICA algorithm based on random grads,this algorithm has advantages such as fast convergence and no necessity for any dynamic parameter,*** algorithm is a highly efficient and reliable method in blind signal separation.

关键词： independent component analysis(ICA) blind source separation fixed-point algorithm

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