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2nd International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)

作者： Zhao Zhi-jin Wang Yang Xu Chun-yun Hangzhou Dianzi Univ Telecommun Engn Sch State Key Lab Informat Control Technol Commun Sys China Elect Technol CorpRes Inst 36 Hangzhou Zhejiang Peoples R China Hangzhou Dianzi Univ Telecommun Engn Sch Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9780769549354

In the light of that the general super-resolution subspace algorithms are invaid to coherent signals and the resolution of singular value decomposition (svd) algorithms is reduced in the presence of low-SNR, an improved svd algorithm to direction-of-arrival (DOA) estimation is proposed. Firstly, a new matrix is constructed from the maximum eigenvector of the signal covariance matrix according to certain rules. Secondly, the reconstruction matrix is corrected by using the idea of matrix decomposition to enhance the decorrelation ability. Finally, ESPRIT method is utilized to DOA estimation. The simulation results show that the proposed algorithm has high estimation success probability, small estimation bias, and low estimation standard error for DOA estimation of the coherent signals in low-SNR condition.

关键词： component DOA estimation coherent signals svd algorithm matrix decomposition

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Application of svd Technology in Video Recommendation System 15

Application of SVD Technology in Video Recommendation System

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15th IEEE/ACIS International Conference on Computer and Information Science (ICIS)

作者： Yan, Menghan Shang, Wenqian Li, Zhenzhong Commun Univ China Sch Comp Sci Beijing Peoples R China

ISBN: (纸本)9781509008056

The most direct access to evaluate what kinds of topics are valuable for video producers, and bring them inspiration is to seek subjects which specific groups concern currently. We can obtain massive user information from social networking platforms, large video sites and search engines, and then exploit the data to produce more practical works with the combination of business requirements. In views of the existing disadvantages of inferior scalability, sparsity problem and huge volume test data, the application of Singular Value Decomposition Method(svd) actualize the unknown prediction score function of set of tests. The simulation results show that scalability, sparsity and omputational efficiency improved effectively.

关键词： svd algorithm collaborative filtering video recommendation matrix decomposition

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Regularization of the inverse heat conduction problem by the discrete Fourier transform

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INVERSE PROBLEMS IN SCIENCE AND ENGINEERING 2016年第2期24卷 195-212页

作者： Wroblewska, Agnieszka Frackowiak, Andrzej Cialkowski, Michal Poznan Univ Tech Chair Thermal Engn Poznan Poland

Two methods of solving the inverse heat conduction problem with employment of the discrete Fournier transform are presented in this article. The first one operates similarly to the svd algorithm and consists in reducing the number of components of the discrete Fournier transform which are taken into account to determine the solution to the inverse problem. The second method is related to the regularization of the solution to the inverse problem in the discrete Fournier transform domain. Those methods were illustrated by numerical examples. In the first example, an influence of the boundary conditions disturbance by a random error on the solution to the inverse problem (its stability) was examined. In the second example, the temperature distribution on the inner boundary of the multiply connected domain was determined. Results of calculations made in both ways brought very good outcomes and confirm the usefulness of applying the discrete Fournier transform to solving inverse problems.

关键词： heat transfer inverse problem svd algorithm Tikhonov regularization Fourier transform

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Image Denoising by Principal Basis Analysis 9

Image Denoising by Principal Basis Analysis

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9th International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR) - Multispectral Image Acquisition, Processing, and Analysis

作者： Sun, Hong Sang, Cheng-Wei Liu, Chen-Guang Wuhan Univ Sch Elect Informat Wuhan 430072 Peoples R China Telecom ParisTech F-75013 Paris France

ISBN: (纸本)9781510600522

This article addresses the image denoising problem in the situations of strong noise. The method we propose is intended to preserve faint signal details under these difficult circumstances. The new method we introduce, called principal basis analysis, is based on a novel criterion: the reproducibility which is an intrinsic characteristic of the geometric regularity in natural images. We show how to measure reproducibility. Then we present the principal basis analysis method, which chooses, in sparse representation of the signal, the components optimizing the reproducibility degree to build a so-called principal basis. With this principal basis, we show that a noise free reconstruction may be obtained. As illustrations, we apply the principal signal basis to image denoising for natural images with details in low signal-to-noise ratio, showing performance better than some reference methods.

关键词： Sparse representation vector norm reproducibility principal components analysis signal basis image denoising svd algorithm

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LARGE svd COMPUTATIONS FOR ANALYSIS OF INVERSE PROBLEMS IN GEOPHYSICS 11

LARGE SVD COMPUTATIONS FOR ANALYSIS OF INVERSE PROBLEMS IN G...

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11th World Congress on Computational Mechanics (WCCM) / 5th European Conference on Computational Mechanics (ECCM) / 6th European Conference on Computational Fluid Dynamics (ECFD)

作者： Solovyev, Sergey A. Tordeux, Sebastien SB RAS Inst Petr Geol & Geophys Novosibirsk 630090 Russia Univ Pau Univ Pau & Pays Adour Inria Bordeaux Sud Ouest Equipe Projet Mag IPRA LMA 3D F-64013 Pau France

ISBN: (纸本)9788494284472

This paper describes the implementation of a new algorithm to compute the Truncated Singular Value Decomposition (T-svd) of matrices with fast decreasing singular values (such as Born approximation matrices). This method is based on a Low-rank approximations which extracts the most important information contained in the matrix. The largest singular values and their left and right singular vectors can then be approximated numerically without performing any operation using the full matrix. This property decreases significantly the memory usage and increases the performance (FLOPS) while getting the T-svd. The low-rank approximation is computed thanks to the Cross Approximation (CA) technique. Validations tests demonstrate the accuracy of the method, both in terms of singular values and singular vectors. High performance of matrix-matrix operations on intermediate steps is archived by using BLAS and LAPACK components from Intel Math Kernel Library (Intel MKL) that is optimized for Intel architecture and parallelized via OpenMP. Performance tests showed more than ten times performance on one-thread system. algorithm has large opportunity for parallelization both on shared memory systems (using OMP parallelization) and on distributed ones (MPI parallelization).

关键词： svd algorithm Cross Approximation (CA) Low-rank approximation High-performance computing Parallel computations

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Least-Squares Iterative Peak-to-Average Ratio Reduction for MIMO-OFDM Systems

Least-Squares Iterative Peak-to-Average Ratio Reduction for ...

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IEEE Global Communications Conference (GLOBECOM)

作者： Wakeel, Abdul Henkel, Werner Jacobs Univ Bremen Transmiss Syst Grp TrSyS D-28759 Bremen Germany

ISBN: (纸本)9781479935123

This manuscript addresses peak-to-average ratio (PAR) reduction in orthogonal frequency division multiplexing (OFDM) based multiple-input multiple-output (MIMO) systems. A new technique for PAR reduction in point-to-point scenarios is proposed. Singular value decomposition (svd) algorithms usually sort the singular values of a MIMO channel in descending order. The last singular value and the associated eigenchannels of a MIMO-OFDM channel are often very weak. Not using them for data transmission will offer redundancy for PAR reduction. These eigenchannels are used to approximate the peaks which exceed a given target value in a least-squares fashion. This approximated exceedence model is then subtracted from the original signal in time domain for PAR reduction. It has been shown that a remarkable gain can be obtained with the proposed algorithm with a negligible increase in the average power and capacity loss.

关键词： MIMO communication OFDM modulation data communication eigenvalues and eigenfunctions iterative methods least squares approximations redundancy singular value decomposition telecommunication network reliability time-domain analysis wireless channels MIMO-OFDM eigenchannel svd algorithm data transmission least square iterative PAR reduction redundancy multiple input multiple output system orthogonal frequency division multiplexing peak-to-average ratio reduction point-to-point scenario singular value decomposition algorithm time domain algorithm design and analysis MIMO Peak to average power ratio Signal to noise ratio Time-domain analysis Vectors Wireless communication

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An Efficient algorithm for Improving Precision of Multi-Cell Channel Estimation Systems

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Procedia Engineering 2012年 41卷 367-376页

作者： Ali K. Marzook A. Ismail B.M. Ali A. Sali S. Khatun Computer andCommunication Systems Department Universiti Putra Malasia Serdang 43400 Malaysia Institute of Advanced Technology Universiti Putra Malasia Serdang 43400 Malaysia School of Computer and Communication System Engineering Universiti Malasia Perlis Malaysia

A new multi-cell joint channel estimation technique for uplink TD-SCDMA system is proposed. The Channel impulse responses of the serving cell and the effective neighboring cell users will process jointly. The new technique adopts the singular value decomposition criterion to reduce the rank order of the system channel matrix. Depending on a limited number of the real parameters that need it to describe the channel matrix, the estimation process will be efficient and the reduced rank technique can significantly improve the channel estimation accuracy. Simulation results show clearly that the proposed reduced rank estimator can significantly improve the channel estimation accuracy for multi-cell networks under rank-deficient consideration. The mean square error (MSE) measure has shown the validity performance of the proposed estimator over the conventional estimators. In addition, the correlation coefficient measures of the reduced rank estimators have shown slightly the superiority of the proposed technique.

关键词： TD-SCDMA systems multi-cell joint channel estimation reduced rank techniques svd algorithm Steiner algorithm

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Numerical Optimization of Cooling Process of the Gas Turbine Blade

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Journal of Chemistry and Chemical Engineering 2011年第4期5卷 355-357页

作者： Andrzej Frackowiak Michal Cialkowski Agnieszka Wroblewska Thermal Engineering Poznan University of Technology Poznan 3 60965 Poland

The paper presents a scheme of optimization of the cooling process of the gas turbine blade. As an optimization criterion has been taken into account on the outer surface temperature of the blade. Inverse problem is solved for stationary heat conduction in which beside the optimization criterion of the heat transfer coefficient on the outer surface of the blade the temperature distribution is known, and the values sought are the heat transfer coefficients and surface temperature of the cooling channels. This problem was solved by the boundary element method using svd algorithm and Tikhonov regularization. The temperature and heat transfer coefficient of cooling channels obtained from the inverse problem was oscillating in nature. This solution is nonphysical, so the heat transfer coefficients on the surface of cooling channels were averaged. Then the problem was solved simply with averaged coefficients of heat transfer on the surface of the cooling channels and the known distribution on the outer surface of blade. The temperature distribution obtained from the solution of direct problem with averaged values of heat transfer coefficient was compared with the criterion of *** calculation results obtained using the svd algorithm gave the temperature distribution on the external wall of the blade closer to the criterion of optimization.

关键词： Inverse problem svd algorithm Tikhonov regularization

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Accuracy of two svd algorithms for 2 x 2 triangular matrices

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APPLIED MATHEMATICS AND COMPUTATION 2009年第1期210卷 232-257页

作者： Hari, V. Matejas, J. Univ Zagreb Fac Econ Zagreb 10000 Croatia Univ Zagreb Dept Math Zagreb 10000 Croatia

A new algorithm for the accurate computation of the singular value decomposition of 2 x 2 triangular matrices is proposed. The algorithm is based on Voevodin formulas. Sharp accuracy bounds are derived by using a subtle error analysis which tracks the signs of the errors of intermediate quantities and does not neglect the non-linear parts of the errors. The analysis is. ne tuned for the case of almost diagonal matrices. The same analysis is also used to analyze the errors for the xLASV2 computational routine of LAPACK. The error estimates of the new algorithm compare favorably to those of the LAPACK routine. (C) 2009 Elsevier Inc. All rights reserved.

关键词： Triangular matrix of order two svd algorithm Error analysis Accuracy

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BACKLASH COMPENSATION USING RECEDING HORIZON CONTROL

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IFAC Proceedings Volumes 2005年第1期38卷 508-513页

作者： María Seron Kyung Sang Yoo Graham Goodwin Centre for Complex Dynamic Systems and Control School of Electrical Engineering and Computer Science The University of Newcastle Callaghan 2308 NSW Australia Department of Electrical Engineering Doowon Technical College Ansung 456-718 Korea

We present a receding horizon control algorithm for compensation of backlash at the input of a stable linear system under control rate constraints. The problem is first posed as a receding horizon optimal control problem by modelling backlash as a piecewise affine system with a state space partition consisting of three regions. This optimal control problem involves solving, at each step, 3 N quadratic programmes, where N is the optimisation horizon. As an alternative to solving the quadratic programmes, we propose a strategy based on a recently devised suboptimal receding horizon control algorithm which utilises a singular value decomposition of the Hessian of the quadratic programme. This alternative strategy leads, at the cost of some performance degradation, to much smaller computational load since a feasible rather than optimal solution has to be obtained at each step.

关键词： Receding horizon control backlash piecewise affine systems rate constraints model predictive control svd algorithm

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