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A fast algorithm for solving diagonally dominant symmetric pentadiagonal Toeplitz systems

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2010年第4期234卷 995-1005页

作者： McNally, Jeffrey Mark St Francis Xavier Univ Dept Math Stat & Comp Sci Antigonish NS B2G 2W5 Canada

Banded Toeplitz systems of linear equations arise in many application areas and have been well studied in the past. Recently, significant advancement has been made in algorithm development of fast parallel scalable methods to solve tridiagonal Toeplitz problems. In this paper we will derive a new algorithm for solving symmetric pentadiagonal Toeplitz systems of linear equations based upon a technique used in [J.M. McNally, L.E. Garey, R.E. Shaw, A split-correct parallel algorithm for solving tri-diagonal symmetric Toeplitz systems, Int. J. Comput. Math. 75 (2000) 303-313] for tridiagonal Toeplitz systems. A common example which arises in natural quintic spline problems will be used to demonstrate the algorithm's effectiveness. Finally computational results and comparisons will be presented. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Toeplitz Pentadiagonal Linear systems fast algorithm Perturbation analysis Natural quintic splines

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A fast algorithm for joint two-dimensional direction of arrival and frequency estimation via hierarchical space-time decomposition

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SIGNAL PROCESSING 2010年第1期90卷 207-216页

作者： Lin, Chun-Hung Fang, Wen-Hsien Lin, Jen-Der Wu, Kuo-Hsiung Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei Taiwan Nan Jeon Inst Technol Dept Elect Engn Tainan Taiwan

In this paper, we present a fast algorithm for joint estimation of the two-dimensional (2-D) directions of arrival (DOAs) and frequencies of the incoming signals in wireless communications using a hierarchical space-time decomposition (HSTD) technique. Based on the HSTD, the proposed algorithm makes use of a sequence of one-dimensional (I-D) Unitary estimation of signal parameters via rotational invariance technique (ESPRIT) algorithms to estimate these parameters alternatively in a hierarchical tree structure. Also, in between every other I-D Unitary ESPRIT algorithm, a temporal filtering process or a spatial beamforming process is invoked to partition the incoming signals into finer groups stage by stage to enhance the estimation accuracy as well as to alleviate the contaminated noise. Furthermore, with such a tree-structured estimation scheme, the pairing of these parameters is automatically determined without extra computational overhead. Simulation results show that the new algorithm provides satisfactory performance but with drastically reduced computations compared with previous works. (C) 2009 Elsevier B.V. All rights reserved.

关键词： 2-D DOA estimation Carrier frequency estimation Joint parameter estimation Unitary ESPRIT fast algorithm

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fast AND ACCURATE BILATERAL FILTERING USING GAUSS-POLYNOMIAL DECOMPOSITION

FAST AND ACCURATE BILATERAL FILTERING USING GAUSS-POLYNOMIAL...

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IEEE International Conference on Image Processing

作者： Kunal N. Chaudhury Department of Electrical Engineering Indian Institute of Science

ISBN: (纸本)9781479983407

The bilateral filter is a versatile non-linear filter that has found diverse applications in image processing, computer vision, computer graphics, and computational photography. A common form of the filter is the Gaussian bilateral filter in which both the spatial and range kernels are Gaussian. A direct implementation of this filter requires O(σ~2) operations per pixel, where σ is the standard deviation of the spatial Gaussian. In this paper, we propose an accurate approximation algorithm that can cut down the computational complexity to O(1) per pixel for any arbitrary σ (constant-time implementation). This is based on the observation that the range kernel operates via the translations of a fixed Gaussian over the range space, and that these translated Gaussians can be accurately approximated using the socalled Gauss-polynomials. The overall algorithm emerging from this approximation involves a series of spatial Gaussian filtering, which can be efficiently implemented (in parallel) using separability and recursion. We present some preliminary results to demonstrate that the proposed algorithm compares favorably with some of the existing fast algorithms in terms of speed and accuracy.

关键词： Bilateral filter Approximation Gauss-polynomial Convolution fast algorithm bilateral filters Convolution approximation Gauss pixel Filters Gaussian filtering fasting Filtration Recursion Approximation algorithms

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fast Analysis of RFIC Using Multilevel Green’s Function Interpolation Method

Fast Analysis of RFIC Using Multilevel Green’s Function Int...

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The 6th International Symposium on Microwave,Antenna,Propagation,and Electromagnetic Compatibility Technologies(MAPE 2015)

作者： Peng Zhao Gaofeng Wang School of Electronics and Information Hangzhou Dianzi University

A full-wave multilevel Green’s function interpolation method（MLGFIM） loop-tree（LP） algorithm based on PMCHWT integral equations is proposed for the fast analysis of EM system in RFIC. To overcome the low-frequency breakdown problem, the LP basis function is adopted to preserve both inductive and capacitive phenomena at very low frequency. PMCHWT integral equations can solve composite metallic and dielectric structures of RFIC with the surface discretization. With the fast algorithm MLGFIM, the computation time and memory are greatly reduced. A spiral inductor example demonstrates its accuracy and efficiency.

关键词： integral equation RFIC full-wave analysis low frequency fast algorithm

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A fast algorithm for Recognizing Translated, Rotated, Reflected, and Scaled Objects from Only their Projections

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IEEE SIGNAL PROCESSING LETTERS 2010年第1期17卷 71-74页

作者： Wan, Yi Wei, Ning Lanzhou Univ Inst Signals & Informat Proc Lanzhou 730000 Peoples R China

The subject of 2-D and higher dimensional object recognition finds widespread applications in areas such as image registration and pattern recognition. Radon transform is one technique used for efficient object matching (e.g., and ). However, so far as we know, no results have been obtained that solves the recognition problem completely in the projection domain due to coupling of transform parameters. We develop a novel method for such parameter decoupling and an improved phase correlation method for accurate practical shift estimation, resulting in a fast matching algorithm based on projection data only. Simulation results show that the proposed algorithm is much faster than similar state-of-the-art approaches such as that in with comparable estimation accuracy.

关键词： fast algorithm medical imaging object recognition pattern recognition phase correlation method radon transform

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Gradient-based subspace phase correlation for fast and effective image alignment

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2014年第7期25卷 1558-1565页

作者： Ren, Jinchang Vlachos, Theodore Zhang, Yi Zheng, Jiangbin Jiang, Jianmin Univ Strathclyde Ctr Excellence Signal & Image Proc Glasgow Lanark Scotland Ionian Univ Dept Audiovisual Arts Corfu Greece Tianjin Univ Sch Comp Software Tianjin Peoples R China Northwestern Polytech Univ Sch Comp Software & Microelect Xian 710072 Peoples R China Shenzhen Univ Sch Comp Sci & Software Engn Shenzhen Peoples R China

Phase correlation is a well-established frequency domain method to estimate rigid 2-D translational motion between pairs of images. However, it suffers from interference terms such as noise and non-overlapped regions. In this paper, a novel variant of the phase correlation approach is proposed, in which 2-D translation is estimated by projection-based subspace phase correlation (SPC). Conventional wisdom has suggested that such an approach can only amount to a compromise solution between accuracy and efficiency. In this work, however, we prove that the original SPC and the further introduced gradient-based SPC can provide robust solution to zero-mean and non-zero-mean noise, and the latter is also used to model the interference term of non-overlapped regions. Comprehensive results from synthetic data and MRI images have fully validated our methodology. Due to its substantially lower computational complexity, the proposed method offers additional advantages in terms of efficiency and can lend itself to very fast implementations for a wide range of applications where speed is at a premium. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Image registration Sub-pixel alignment Phase correlation Interference terms Subspace projection Fourier transform Motion estimation fast algorithm

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fast numerical method for crack problem in the porous elastic material

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MECCANICA 2014年第9期49卷 2169-2179页

作者： Popuzin, V. Pennisi, M. Univ Catania DMI I-95125 Catania Italy

The present paper discusses the crack problem in the linear porous elastic plane using the model developed by Nunziato and Cowin. With the help of Fourier transform the problem is reduced to an integral equation over the boundary of the crack. Some analytical transformations are applied to calculate the kernel of the integral equation in its explicit form. We perform a numerical collocation technique to solve the derived hyper-singular integral equation. Due to convolution type of the kernel, we apply, at each iteration step, the classical iterative conjugate gradient method in combination with the fast Fourier technique to solve the problem in almost linear time. There are presented some numerical examples for materials of various values of porosity.

关键词： Crack problem Porous material fast algorithm Hyper-singular equation

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A fast algorithm of Building Interfirm Collaboration Network

A Fast Algorithm of Building Interfirm Collaboration Network

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2nd International Conference on Computer and Automation Engineering (ICCAE)

作者： Wen, Zhou Yan, Zhao Yao, Li Shanghai Univ Sch Comp Engn & Sci Shanghai Peoples R China Shanghai Univ Sch Management Shanghai Peoples R China

There are many scholars doing research on interfirm network. But most of them construct the network manually. The fast algorithm of building interfirm collaboration network is constructed in this paper. The algorithm ... 详细信息

ISBN: (纸本)9781424455690

关键词： complex network interfirm network fast algorithm social network

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Time-Varying AR Spectral Estimation Using an Indefinite Matrix-Based Sliding Window fast Linear Prediction

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2014年第2期E97A卷 547-556页

作者： Nishiyama, Kiyoshi Iwate Univ Fac Engn Dept Elect Engn & Comp Sci Morioka Iwate 0208551 Japan

A method for efficiently estimating the time-varying spectra of nonstationary autoregressive (AR) signals is derived using an indefinite matrix-based sliding window fast linear prediction (ISWFLP). In the linear prediction, the indefinite matrix plays a very important role in sliding an exponentially weighted finite-length window over the prediction error samples. The resulting ISWFLP algorithm successively estimates the time-varying AR parameters of order N at a computational complexity of O(N) per sample. The performance of the AR parameter estimation is superior to the performances of the conventional techniques, including the Yule-Walker, covariance, and Burg methods. Consequently, the ISWFLP-based AR spectral estimation method is able to rapidly track variations in the frequency components with a high resolution and at a low computational cost. The effectiveness of the proposed method is demonstrated by the spectral analysis results of a sinusoidal signal and a speech signal.

关键词： spectral estimation autoregressive model linear prediction fast algorithm sliding window indefinite matrix forgetting factor

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A fast algorithm for Constrained GLAD Estimation with Application to Image Restoration

A Fast Algorithm for Constrained GLAD Estimation with Applic...

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8th World Congress on Intelligent Control and Automation (WCICA)

作者： Xia, Youshen Fuzhou Univ Coll Math & Comp Sci Fuzhou 350002 Peoples R China

ISBN: (纸本)9781424467129

In order to relax need of the optimal regularization parameter to be estimated, a cooperative recurrent neural network (CRNN) algorithm for image restoration was presented by solving a generalized least absolute deviation ( GLAD) problem. This paper proposes a fast algorithm for solving a constrained l(1)-norm problem which contains the GLAD problem as its special case. The proposed iterative algorithm is guaranteed to converge globally to an optimal estimate under a fixed step length. Compared with the CRNN algorithm being continuous time, the proposed iterative algorithm has a fast convergence speed. Illustrative examples with application to image restoration show that the proposed iterative algorithm has a much faster convergence rate than the CRNN algorithm.

关键词： GLAD estimate constrained l(1)-norm problem fast algorithm image restoration

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