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Low-complexity conjugate gradient algorithm for array code acquisition

IEICE TRANSACTIONS ON COMMUNICATIONS 2007年第5期E90B卷 1193-1200页

作者： Yang, Hua-Lung Wu, Wen-Rong Natl Chiao Tung Univ Dept Commun Engn Hsinchu Taiwan

An adaptive array code acquisition for direct-sequence/ code-division multiple access (DS/CDMA) systems was recently proposed to enhance the performance of the conventional correlator-based method. The scheme consists of an adaptive spatial and an adaptive temporal filter, and can simultaneously perform beamforming and code-delay estimation. Unfortunately, the scheme uses a least-mean-square (LMS) adaptive algorithm, and its convergence is slow. Although the recursive-least-squares (RLS) algorithm can be applied, the computational complexity will greatly increase. In this paper, we solve the dilemma with a low-complexity conjugate gradient (LCG) algorithm, which can be considered as a special case of a modified conjugate gradient (MCG) algorithm. Unlike the original conjugate gradient (CG) algorithm developed for adaptive applications, the proposed method, exploiting the special structure inherent in the input correlation matrix, requires a low computational-complexity. It can be shown that the computational complexity of the proposed method is on the same order of the LMS algorithm. However, the convergence rate is improved significantly. Simulation results show that the performance of adaptive array code acquisition with the proposed CG algorithm is comparable to that with the original CG algorithm.

关键词： code acquisition synchronization DS/CDMA antenna arrays adaptive filtering conjugate gradient algorithm

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A New Approach to Load Flow Analysis using Krylov Subspace Methods for well conditioned systems

A New Approach to Load Flow Analysis using Krylov Subspace M...

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Annual IEEE India Conference - Engineering Sustainable Solutions

作者： Saha, Debarshi Singha, Souvik Bengal Inst Technol & Management Dept Elect Engn Santini Ketan 731236 W Bengal India Bengal Inst Technol & Management Dept Comp Sci & Informat Santini Ketan 731236 W Bengal India

ISBN: (纸本)9781457711091

Power system load flow analysis mainly utilizes the Gauss-Seidel method, the Newton-Raphson method, and the Fast Decoupled Load Flow method. All these stationary iterative algorithms assure convergence for a limited class of well-conditioned matrices, and require a good enough estimate of nodal voltages at all system busbars under consideration, to provide assured convergence. The Krylov subspace methods are widely generalized in their approach, and work by forming an orthogonal basis of the sequence of successive matrix powers times the initial residual (the Krylov sequence). The prototypical method in this class is the conjugate gradient method (CG). In this work, we propose to apply the conjugate gradient algorithm to the sparse systems;we encounter these in the system admittance matrices, and we will search for a numerical solution to this system using the locally optimal steepest descent method. The system admittance matrices for an IEEE 30-bus or 57-bus system(s) are too large to be handled by direct methods like the Cholesky decomposition method. Hence, we will make use of the flexible preconditioned conjugate-gradient method, which makes use of sophisticated preconditioners, leading to variable preconditioning that change between successive iterations. The Polak-Ribiere formula, a highly efficient preconditioner, is applied to the system, to yield drastic improvements in convergence. Our experimental results include a comparison of the Krylov subspace method with traditional methods, assuming the IEEE five-busbar, seven-line reference system as the common basis for all load-flow analysis. The system base quantities are VA(base)=100 MVA and V-base=132 kV. The results show an overall better assurance of convergence for all general systems, a lesser dependence on starting voltage profiles assumption and a robustness and efficiency of computation for well-conditioned systems.

关键词： Krylov subspace methods conjugate gradient algorithm preconditioners Polak-Ribiere formula assured convergence

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Internal surfaces including phase change materials for passive optimal shift of solar heat gain

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INTERNATIONAL JOURNAL OF THERMAL SCIENCES 2010年第11期49卷 2148-2156页

作者： Arnault, Axel Mathieu-Potvin, Francois Gosselin, Louis Univ Laval Dept Genie Mecan Quebec City PQ G1V 0A6 Canada

The thermal inertia of building internal components may be used to shift the irradiation (solar) heat load, which could result in substantial energy saving. In this paper, a numerical model was implemented to determine the thermal performance of internal surfaces including Phase Change Materials (PCM). The model was exploited to compare a typical concrete floor with a floor with PCM. Thermal performance was defined by three different objective functions, each pinpointing different thermal characteristics of the heat load. First, parametric studies were performed to understand the influence of the thickness of a typical concrete floor. Then, the optimization of the melting temperature, thickness and position of a PCM layer included in a floor was performed. These analyses used either simplified or real weather conditions (for Quebec City). Results showed that the thickness of the concrete floor could be optimized based on the three criteria retained. Also, the floor performance may be enhanced by the inclusion of a PCM layer. It was shown that the gain of performance brought by the internal surfaces thermal mass strongly depends on the weather conditions considered. This paper provides a fundamental understanding of PCM influence on internal surfaces. (C) 2010 Elsevier Masson SAS. All rights reserved.

关键词： Floor conjugate gradient algorithm Solar heat gain Phase change material HVAC Optimization

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Inverse methodology to determine mold set-point temperature in resin transfer molding process

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INTERNATIONAL JOURNAL OF THERMAL SCIENCES 2010年第11期49卷 2138-2147页

作者： Sobotka, Vincent Lefevre, Nicolas Jarny, Yvon Delaunay, Didier Nantes Atlantique Univ Ecole Polytech Univ Nantes Lab Thermocinet Nantes UMR CNRS 6607 F-44306 Nantes 03 France

This study consists of determining by inverse method the set-point temperature of the fluid flowing through heating plates in a Resin Transfer Molding (RIM) process tool so as to reach a predetermined thermal history in the composite part. Although the described methodology is applied in a specific mold in this paper, it remains general and may be transposed to a large scale of molding configuration. The considered mold is metallic and composed of several parts. Assembling these parts is not possible without introducing imperfect contacts that perturb heat transfer between them. The heat transfer at the interface is modeled by thermal contact resistances (TCR) whose values are unknown. In the case of metallic molds TCR are of the same order of magnitude than the equivalent thermal resistance of the mold. Therefore they cannot be neglected. The influence of these TCR is then a key-point on heat transfer since a bad knowledge of their values implies a wrong estimation of the temperature field. Then before being able to estimate the set-point of the temperature of the thermoregulated fluid, it is necessary in a first stage to evaluate the most influent TCR that are spatially and time dependent. Their determination is achieved by an optimization approach and carried out on a 2D transverse cut of the mold. Experimental temperature measurements in the mold are matched to the computed responses of the heat conduction model. A least square criterion is minimized by using the conjugate gradient algorithm. The gradient of the criterion is determined by solving a set of adjoint equations. After the identification of these parameters, the same optimization method is used to compute the mold set point temperature. It is notable that the same set of adjoint equations is used to solve both problems. (C) 2010 Elsevier Masson SAS. All rights reserved.

关键词： Resin transfer molding Inverse method Adjoint problem Composite material Two dimensional heat transfer Parameter estimation conjugate gradient algorithm Thermal control

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Time-harmonic solution for acousto-elastic interaction with controllability and spectral elements

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2010年第6期234卷 1904-1911页

作者： Monkola, Sanna Univ Jyvaskyla Dept Math Informat Technol FI-40014 Jyvaskyla Finland

The classical way of solving the time-harmonic linear acousto-elastic wave problem is to discretize the equations with finite elements or finite differences. This approach leads to large-scale indefinite complex-valued linear systems. For these kinds of systems, it is difficult to construct efficient iterative solution methods. That is why we use an alternative approach and solve the time-harmonic problem by controlling the solution of the corresponding time dependent wave equation. In this paper, we use an unsymmetric formulation, where fluid-structure interaction is modeled as a coupling between pressure and displacement. The coupled problem is discretized in space domain with spectral elements and in time domain with central finite differences. After discretization, exact controllability problem is reformulated as a least-squares problem, which is solved by the conjugate gradient method. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Fluid-structure interaction Acoustic waves Elastic waves Coupled problem Time-harmonic solution Spectral element method Controllability conjugate gradient algorithm

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Accelerating Numerical Linear Algebra Kernels on a Scalable Run Time Reconfigurable Platform

Accelerating Numerical Linear Algebra Kernels on a Scalable ...

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IEEE Annual Symposium on VLSI (ISVLSI)

作者： Biswas, Prasenjit Udupa, Pramod P. Mondal, Rajdeep Varadarajan, Keshavan Alle, Mythri Nandy, S. K. Narayan, Ranjani CADL IISc Bangalore Karnataka India Morphing Machines Bangalore Karnataka India

ISBN: (纸本)9780769540764

Numerical Linear Algebra (NLA) kernels are at the heart of all computational problems. These kernels require hardware acceleration for increased throughput. NLA Solvers for dense and sparse matrices differ in the way the matrices are stored and operated upon although they exhibit similar computational properties. While ASIC solutions for NLA Solvers can deliver high performance, they are not scalable, and hence are not commercially viable. In this paper, we show how NLA kernels can be accelerated on REDEFINE, a scalable runtime reconfigurable hardware platform. Compared to a software implementation, Direct Solver (Modified Faddeev's algorithm) on REDEFINE shows a 29x improvement on an average and Iterative Solver (conjugate gradient algorithm) shows a 15-20% improvement. We further show that solution on REDEFINE is scalable over larger problem sizes without any notable degradation in performance.

关键词： ASIC solutions conjugate gradient Direct Solver Faddeev's algorithm Iterative Solver NLA kernels NLA solvers Numerical Linear Algebra REDEFINE Runtime reconfiguration Systolic array computational property conjugate gradient algorithm conjugate gradient methods dense matrices direct solver hardware acceleration linear algebra modified Faddeev's algorithm numerical linear algebra kernels reconfigurable architectures scalable run time reconfigurable platform software implementation sparse matrices sparse matrices

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Complex Blind Source Separation via Simultaneous Strong Uncorrelating Transform 1

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9th International Conference on Latent Variable Analysis and Signal Separation

作者： Shen, Hao Kleinsteuber, Martin Tech Univ Munich Inst Data Proc D-8000 Munich Germany

ISBN: (数字)9783642159954

ISBN: (纸本)9783642159947

In this paper, we address the problem of complex blind source separation (BSS), in particular, separation of nonstationary complex signals. It is known that, under certain conditions, complex BSS can be solved effectively by the so-called Strong Uncorrelating Transform (SUT), which simultaneously diagonalizes one Hermitian positive definite and one complex symmetric matrix. Our current work generalizes SUT to simultaneously diagonalize more than two matrices. A conjugate gradient (CG) algorithm for computing simultaneous SUT is developed on an appropriate manifold setting of the problem, namely complex oblique projective manifold. Performance of our method, in terms of separation quality, is investigated by several numerical experiments.

关键词： Complex blind source separation nonstationary signal simultaneous strong uncorrelating transform complex oblique projective manifold conjugate gradient algorithm

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Fast Bayesian Estimation for VARFIMA Processes with Stable Errors

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JOURNAL OF STATISTICAL THEORY AND PRACTICE 2010年第4期4卷 663-677页

作者： Pai, Jeffrey S. Ravishanker, Nalini Univ Manitoba Warren Ctr Actuarial Studies & Res Winnipeg MB R3T 5V4 Canada Univ Connecticut Dept Stat Storrs CT 06269 USA

We present an approach via a multivariate preconditioned conjugate gradient (MPCG) algorithm for Bayesian inference for vector ARFIMA models with sub-Gaussian stable errors. This approach involves solution of a block-Toeplitz system, and treating the unobserved process history and the underlying positive stable process as unknown parameters in the joint posterior. We use Gibbs sampling with the Metropolis-Hastings algorithm. We illustrate our approach on time series of daily average temperatures measured over several years at different U.S. cities.

关键词： Autoregressive fractionally integrated moving average model conjugate gradient algorithm Fast Fourier transform Markov chain Monte Carlo Preconditioning Sub-Gaussian stable errors

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Time-harmonic solution for acousto-elastic interaction with controllability and spectral elements

Time-harmonic solution for acousto-elastic interaction with ...

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8th International Conference on Mathematical and Numerical Aspects of Waves

作者： Monkola, Sanna Univ Jyvaskyla Dept Math Informat Technol FI-40014 Jyvaskyla Finland

关键词： Fluid-structure interaction Acoustic waves Elastic waves Coupled problem Time-harmonic solution Spectral element method Controllability conjugate gradient algorithm

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New results on the convergence of the conjugate gradient method

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NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS 2009年第3期16卷 223-236页

作者： Bouyouli, R. Meurant, G. Smoch, L. Sadok, H. Zone Univ Mivoix Univ Littoral Lab Math Pures & Appl F-62228 Calais France CEA DIF F-91680 Bruyeres Le Chatel France Univ Mohammed 5 Dept Math Fac Sci Rabat Morocco

This paper is concerned with proving theoretical results related to the convergence of the conjugate gradient (CG) method for solving positive definite symmetric linear systems. Considering the inverse of the projection of the inverse of the matrix, new relations for ratios of the A-norm of the error and the norm of the residual are provided, starting from some earlier results of Sadok (Numer algorithms 2005;40:201-216). The proofs of our results rely on the well-known correspondence between the CG method and the Lanczos algorithm. Copyright (C) 2008 John Wiley & Sons, Ltd.

关键词： symmetric linear systems conjugate gradient algorithm Lanczos algorithm Krylov subspace Ritz values

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