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Improved preconditioned conjugate gradient algorithm and application in 3D inversion of gravity-gradiometry data

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Applied Geophysics 2017年第2期14卷 301-313,324页

作者： Wang Tai-Han Huang Da-Nian Ma Guo-Qing Meng Zhao-Hai Li Ye College of Geo-Exploration Scienceand Technology Jilin University Claangchun 130021 China Tianjin Navigation Instrument Research Institute Tianjin 300131 China Jilin Provincial Electric Power Survey and Design Institute Changchun 130021 China.

With the continuous development of full tensor gradiometer （FTG） measurement techniques, three-dimensional （3D） inversion of FTG data is becoming increasingly used in oil and gas exploration. In the fast processing and interpretation of large-scale high-precision data, the use of the graphics processing unit process unit （GPU） and preconditioning methods are very important in the data inversion. In this paper, an improved preconditioned conjugate gradient algorithm is proposed by combining the symmetric successive over-relaxation （SSOR） technique and the incomplete Choleksy decomposition conjugate gradient algorithm （ICCG）. Since preparing the preconditioner requires extra time, a parallel implement based on GPU is proposed. The improved method is then applied in the inversion of noise- contaminated synthetic data to prove its adaptability in the inversion of 3D FTG data. Results show that the parallel SSOR-ICCG algorithm based on NVIDIA Tesla C2050 GPU achieves a speedup of approximately 25 times that of a serial program using a 2.0 GHz Central Processing Unit （CPU）. Real airbome gravity-gradiometry data from Vinton salt dome （south- west Louisiana, USA） are also considered. Good results are obtained, which verifies the efficiency and feasibility of the proposed parallel method in fast inversion of 3D FTG data.

关键词： Full Tensor Gravity Gradiometry (FTG) ICCG method conjugate gradient algorithm gravity-gradiometry data inversion CPU and GPU

P-norm Regularized SVM Classifier by Non-convex conjugate gradient algorithm

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P-norm Regularized SVM Classifier by Non-convex Conjugate Gr...

A Hybrid conjugate gradient algorithm for Solving Relative Orientation of Big Rotation Angle Stereo Pair

第25届中国控制与决策会议

作者： ZUO Xin HUANG Hailong LI Haien LIU Jianwei Research Institute of Automation China University of Petroleum

ISBN: (纸本)9781467355339

Classical classification algorithm of SVM via p norm regularization usually takes p as 0, 1 or 2. However, these parameters can’t always achieve the best classification results. Some scholars have discussed the situations of p∈{0,1, 2} , where the problem is transformed into the standard quadratic programming. However, when p∈(0,1], the object is non-convex, and the method of quadratic programming is not suitable. From the point of optimization, we use conjugate gradient algorithm to solve the problem. In this paper, two different kinds of SVM have been discussed and the classification results are shown by the experiments on three cancer datasets. At last, we discussed the problem of feature selection. The experiment results show that, feature selection can not only keep the precision of the prediction but also reduce model complexity.

关键词： Lp-norm 0 SVM conjugate gradient algorithm Feature Selection

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Journal of Geodesy and Geoinformation Science 2020年第2期3卷 62-70页

作者： Jiatian LI Congcong WANG Chenglin JIA Yiru NIU Yu WANG Wenjing ZHANG Huajing WU Jian LI Faculty of Land Resource Engineering Kunming University of Science and TechnologyKunming 650093China Surveying and Mapping Geo-Informatics Technology Research Center Plateau Mountains of Yunnan Higher Education of Kunming University of Science and TechnologyKunming 650093China

The fast convergence without initial value dependence is the key to solving large angle relative ***,a hybrid conjugate gradient algorithm is proposed in this *** concrete process is:①stochastic hill climbing(SHC)algorithm is used to make a random disturbance to the given initial value of the relative orientation element,and the new value to guarantee the optimization direction is generated.②In local optimization,a super-linear convergent conjugate gradient method is used to replace the steepest descent method in relative orientation to improve its convergence rate.③The global convergence condition is that the calculation error is less than the prescribed limit *** comparison experiment shows that the method proposed in this paper is independent of the initial value,and has higher accuracy and fewer iterations.

关键词： relative orientation big rotation angle global convergence stochastic hill climbing conjugate gradient algorithm

A Note on Global Convergence Result for conjugate gradient Methods

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Journal of Shanghai University(English Edition) 2001年第1期5卷 15-19页

作者： BAI Yan qin Department of Mathematics, College of Sciences, Shanghai University, Shanghai 200436, China Department of Mathematics College of Sciences Shanghai University Shanghai China

We extend a results presented by Y.F. Hu and *** (1991) [1] on the global convergence result for conjugate gradient methods with different choices for the parameter β k . In this note, the conditions ... 详细信息

关键词： conjugate gradient algorithm descent property global convergence restarting

Krylov subspace method based on data preprocessing technology

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Journal of Systems Engineering and Electronics 2008年第6期19卷 1063-1069页

作者： Tang Bin Wang Xuegang Zhang Chaoshen Chen Kesong School of Electronic Engineering Univ. of Electronic Science and Technology of China Chengdu 610054 P. R. China Chengdu Aircraft Design & Research Inst. Chengdu 610041 P. R. China

The performance of adaptive beamforming techniques is limited by the nonhomogeneous clutter scenario. An augmented Krylov subspace method is proposed, which utilizes only a single snapshot of the data for adaptive processing. The novel algorithm puts together a data preprocessor and adaptive Krylov subspace algorithm, where the data preprocessor suppresses discrete interference and the adaptive Krylov subspace algorithm suppresses homogeneous clutter. The novel method uses a single snapshot of the data received by the array antenna to generate a cancellation matrix that does not contain the signal of interest （SOI） component, thus, it mitigates the problem of highly nonstationary clutter environment and it helps to operate in real-time. The benefit of not requiring the training data comes at the cost of a reduced degree of freedom （DOF） of the system. Simulation illustrates the effectiveness in clutter suppression and adaptive beamforming. The numeric results show good agreement with the proposed theorem.

关键词： adaptive beamforming Krylov subspace conjugate gradient algorithm nonhomogeneous clutter clutter suppress

SINE TRANSFORM MATRIX FOR SOLVING TOEPLITZ MATRIX PROBLEMS

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Journal of Computational Mathematics 2001年第2期19卷 167-176页

作者： Li-zhi Cheng (Department of Mathematics & System Sciences, National University of Defence Technology, Changsha 410073, China) 国防科技大学湖南长沙 410073

Provides information on a study which discussed the properties of eigenvalues for the solutions of symmetric positive definite Toeplitz systems, skew circulant and sine transform based properties. Eigenvalues of various preconditioners; Design of positive sine transform based preconditioners; Clustering property of the preconditioners; Numerical results.

关键词： preconditioner Toeplitz systems the fast sine transform conjugate gradient algorithm

A Numerical Method for Cavity Identification in Beams on an Elastic Foundation

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Tsinghua Science and Technology 2007年第5期12卷 540-545页

作者：葛洪海许金余 School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University

An analytical solution for the natural frequencies of a beam containing a cavity on an elastic foundation is presented. Based on the analytical solution, a numerical method for identifying cavities in the foundation is developed. The position and size of the cavities are identified by minimizing an objective function, which is formulated according to the difference between the computed and measured natural frequencies of the system. The conjugate gradient algorithm is adopted for minimizing the objective function. Some numerical examples are presented to demonstrate the applicability of the presented cavity determination method. The results show that the presented method can be used to identify the cavity position and size conveniently and efficiently.

关键词： pavement-subgrade system beam on an elastic foundation cavity identification natural frequency conjugate gradient algorithm

Neural Volterra filter for chaotic time series prediction

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Chinese Physics B 2005年第11期14卷 2181-2188页

作者：李恒超张家树肖先赐 Sichuan Province Key Laboratory of Signal and Information Processing Southwest Jiaotong University Chengdu 610031 China Department of Electronic Engineering University of Electronic Science and Technology of China Chengdu 610054 China

A new second-order neural Volterra filter （SONVF） with conjugate gradient （CG） algorithm is proposed to predict chaotic time series based on phase space delay-coordinate reconstruction of chaotic dynamics system in this paper, where the neuron activation functions are introduced to constraint Volterra series terms for improving the nonlinear approximation of second-order Volterra filter （SOVF）. The SONVF with CG algorithm improves the accuracy of prediction without increasing the computation complexity. Meanwhile, the difficulty of neuron number determination does not exist here. Experimental results show that the proposed filter can predict chaotic time series effectively, and one-step and multi-step prediction performances are obviously superior to those of SOVF, which demonstrate that the proposed SONVF is feasible and effective.

关键词： chaotic time series adaptive neural Volterra filter conjugate gradient algorithm

Blind Equalization Using a Novel Recurrent Neural Network Training algorithm

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The Journal of China Universities of Posts and Telecommunications 1997年第2期4卷 47-49页

作者： LiangQilian ZhouZheng 等 CollegeofTelecomEngineering BeijingUniversityofPostsandTelecommunicationsBeijing100876P.RChina Coll

A novel Recurrent Neural Network(RNN) based blind equalization algorithm is proposed in the *** the first time, the conjugate gradient algorithm and a three point searching method are used in RNN *** results show th... 详细信息

关键词： blind equalization conjugate gradient algorithm three point searching method