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An Accelerated Nonlinear Contrast Source Inversion Scheme for Sparse Electromagnetic Imaging

IEEE ACCESS 2021年 9卷 54811-54819页

作者： Sandhu, Ali Imran Desmal, Abdulla Bagci, Hakan King Abdullah Univ Sci & Technol KAUST Div Comp Elect & Math Sci & Engn CEMSE Thuwal 239556900 Saudi Arabia Higher Coll Technol HCT Dept Elect Engn Ras Al Khaymah U Arab Emirates

An efficient nonlinear contrast source inversion scheme for electromagnetic imaging of sparse two-dimensional investigation domains is proposed. To avoid generating a sequence of linear sparse optimization problems, the non-linearity is directly tackled using the nonlinear Landweber (NLW) iterations. A self-adaptive projected accelerated steepest descent (A-PASD) algorithm is incorporated to enhance the efficiency of the NLW iterations. The algorithm enforces the sparsity constraint by projecting the result of each steepest descent iteration into the L-1 -norm ball and selects the largest-possible iteration step without sacrificing from convergence. Numerical results, which demonstrate the proposed scheme's accuracy, efficiency, and applicability, are presented.

关键词： Contrast source inversion electromagnetic imaging inverse problems Landweber iterations nonlinear inverse scattering sparse reconstruction steepest descent algorithm

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A New Assisted History Matching Approach for Complex Reservoirs

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ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS 2015年第18期37卷 1954-1961页

作者： Dang, T. Q. C. Chen, Z. Nguyen, T. B. N. Bae, W. Phung, T. H. Univ Calgary Dept Chem & Petr Engn Calgary AB T2N 1N4 Canada Sejong Univ Dept Energy & Mineral Resources Engn Seoul 143747 South Korea Vietsovpetro JV Res & Engn Inst Vung Tau City Vietnam

This article describes the integration of mathematical models (Simplex and steepest descent algorithm) with global modification (through deeply geological studies) to increase the efficiency of history matching. This method can take full advantage of the gradient-based method (fast rate of convergence) and guarantee of finding a global minimum for inverse problems. The above method is applied to the Lower Miocene reservoir at White Tiger field, a highly heterogeneous reservoir, which has been producing under a naturally edge-water mechanism. A model that covers the upper formation of White Tiger field with 27 production wells and 8 injection wells is conditioned to 23 years of production history. The new assisted history matching approach provides an excellent match between simulation results and production data.

关键词： assisted history matching global optimization gradient-based method simplex algorithm steepest descent algorithm

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Output tracking control of non-minimum phase systems using on-line output redefinition approach based on barrier function method

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IET CONTROL THEORY AND APPLICATIONS 2022年第15期16卷 1518-1530页

作者： Jahangiri, Fatemeh Yadegar, Meysam Shahid Beheshti Univ Dept Elect Engn Tehran Iran Qom Univ Technol Dept Elect & Comp Engn Qom Iran

This paper considers the output tracking problem of non-minimum phase non-linear systems using the inverse dynamics control which is impossible in conventional methods due to unstable zero dynamics. The proposed method is based on the output redefinition approach defined as a parametric function. The tracking error is decomposed into two terms. The first one named redefined output tracking error is the difference between the redefined output and the reference signal, and the second one is the distance between the redefined output and the system output. For the first term, due to minimum phase property of the system with the redefined output, an inverse dynamics control is used to guarantee the convergence of the redefined output tracking error to zero. To minimize the second term, the parameters of the redefined output are set by solving an optimization problem whose constraints include minimum phase conditions. To solve the optimization problem which satisfies all constraints, the barrier function method as an interior point method is adopted. The optimization parameters are set using steepest descent algorithm. Due to on-line updating the redefined output parameters, the related zero dynamics is time varying. Therefore, sufficient conditions for exponential stability of the resulting time-varying zero dynamics are obtained.

关键词： convergence inverse dynamics control barrier function method online output redefinition approach exponential stability asymptotic stability steepest descent algorithm minimum phase property optimisation tracking output tracking control minimum phase conditions redefined output tracking error time-varying zero dynamics nonminimum phase nonlinear systems inverse problems nonlinear control systems

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CUMULANT-BASED PARAMETER-ESTIMATION USING STRUCTURED NETWORKS

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IEEE TRANSACTIONS ON NEURAL NETWORKS 1991年第1期2卷 73-83页

作者： WANG, LX MENDEL, JM Signal and Image Processing Institute Department of Electrical Engineering-Systems University of Southern California Los Angeles CA USA

This paper develops a two-level three-layer structured network to estimate the moving-average (MA) model parameters based on second-order and third-order cumulant matching. The structured network is a multilayer feedforward network composed of linear summers, in which the weights of these summers have a clear physical meaning. The first level is composed of random access memory (RAM) units, which are used to control the connectivities of the second-level summers. The second level is composed of three layers of linear summers in which the weight of any summer represents the moving-average parameter to be estimated. The connectivities among these summers are controlled by the first-level memory units in such a way that the outputs of the second-level structured network will equal the desired second-order or third-order statistics if the summer weights equal their corresponding true moving-average parameter values. Each second-order and third-order cumulant is viewed as a pattern which the structured network needs to learn, and a steepest descent algorithm is proposed for training the structured network. This paper also presents extensions to input statistic estimation, moving-average order determination, auto-regressive moving-average (ARMA) parameter estimation, and parameter estimation based on fourth-order cumulants. Simulations demonstrate the performance of these structured network approaches.

关键词： model parameters feedforward network Equal Parameter estimation summer steepest descent algorithm NETWORK STRUCTURE Network random access machine

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Lie Group Method: A New Approach to Image Matching with Arbitrary Orientations

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INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY 2010年第3期20卷 245-252页

作者： Ying, Shihui Qiao, Hong Shanghai Univ Sch Sci Dept Math Shanghai 200444 Peoples R China Chinese Acad Sci Inst Automat Key Lab Complex Syst & Intelligent Sci Beijing 100080 Peoples R China

In this article, we develop a new method for image matching of any two images with arbitrary orientations. The idea comes from the workpiece localization in machining industry. We first describe an image as a 3D point set other than the common 2D function f(x, y), then, making the sets corresponding to the compared images form solid surfaces, we equivalently translate the matching problem into an optimization problem on the Lie group SE(3). Through developing a kind of steepest descent algorithms on a general Lie group, we present an practical algorithm for matching problem. Simulations of eye detection and face detection are presented to show the feasibility and efficiency of the proposed algorithm. (C) 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 245-252, 2010;View this article online at ***. DOI 10.1002/ima.20244

关键词： template matching Lie groups Lie algebras steepest descent algorithm

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Precoding Scheme Robust to Imperfect CSI in Downlink Multiuser MIMO-OFDM System

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IEICE TRANSACTIONS ON COMMUNICATIONS 2011年第12期E94B卷 3515-3524页

作者： Chang, Linchen Fukawa, Kazuhiko Suzuki, Hiroshi Suyama, Satoshi Tokyo Inst Technol Tokyo 1528550 Japan

This paper proposes a precoding scheme for downlink multiuser MIMO-OFDM systems. The proposed precaling employs the minimum average bit error rate (MABER) criterion, and obtains precoding matrices by the steepest descent algorithm in order to minimize average BER of mobile stations. As the cost function of the proposed scheme, an upper bound of the average BER is derived from the pairwise error probability (PEP) and is averaged with respect to channel state information (CSI) errors. Thus, the MABER scheme is robust against imperfect CSI. Computer simulations under a frequency-selective fading condition demonstrate that the proposed precoder is more robust against the CSI errors than both the zero-forcing (ZF) precoder and a robust sum mean square error (SMSE) precder, and that it is superior in BER to the conventional schemes.

关键词： multiuser MIMO MIMO-OFDM precoding imperfect channel state information steepest descent algorithm

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Proportionate adaptive algorithms for network echo cancellation

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2006年第5期54卷 1794-1803页

作者： Deng, HY Doroslovacki, M George Washington Univ Dept Elect & Comp Engn Washington DC 20052 USA

By analyzing the coefficient adaptation process of the steepest descent algorithm, the condition under which the fastest overall convergence will be achieved is obtained and the way to calculate optimal step-size control factors to satisfy that condition is formulated. Motivated by the results and using the stochastic approximation paradigm, the mu-law PNLMS (MPNLMS) algorithm is proposed to keep, in contrast to the proportionate normalized least-mean-square (PN-LMS) algorithm, the fast initial convergence during the whole adaptation process in the case of sparse echo path identification. Modifications of the MPNLMS algorithm are proposed to lower the computational complexity.

关键词： adaptive filtering convergence network echo cancellation proportionate normalized least mean square (PNLMS) algorithm sparse impulse response steepest descent algorithm stochastic approximation

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Improving convergence of the PNLMS algorithm for sparse impulse response identification

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IEEE SIGNAL PROCESSING LETTERS 2005年第3期12卷 181-184页

作者： Deng, HY Doroslovacki, M George Washington Univ Dept Elect & Comp Engn Washington DC 20052 USA

A proportionate normalized least mean square (PNLMS) algorithm has been proposed for sparse impulse response identification. It provides fast initial convergence, but it begins to slow down dramatically after the initial period. In this letter, we analyze the coefficient adaptation process of the steepest descent algorithm and derive how to calculate the optimal proportionate step size in order to achieve the fastest convergence. The results bring forward a novel view of the concept of proportion. We propose a mu-law PNLMS (MPNLMS) algorithm using an approximation of the optimal proportionate step size. Line segment approximation and partial update techniques are discussed to bring down the computational complexity.

关键词： adaptive filtering convergence network echo cancellation proportionate normalized least mean square (PNLMS) algorithm steepest descent algorithm

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Spare supply system for Globalstar, a worldwide telecommunication system

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COMPUTERS & INDUSTRIAL ENGINEERING 1999年第1-2期37卷 265-268页

作者： Ushakov, I Antonov, S Chakravarty, S Hamid, A Keliinoi, T QUALCOMM INC San Diego CA USA Russian Acad Sci Moscow Russia

This work describes the Optimal Spare Allocator (OSA), a overdot software tool for Globalstar, which is a worldwide satellite telecommunication system designed at QUALCOMM (San Diego, USA). The Globalstar spare supply system is hierarchical and has three levels: Central Spare Stock (CSS), Regional Spare Stocks (RSS) and On-Site Spare Stocks (OSS). OSS is destined to supply spares to a Globalstar base station (gateway). The tool allows us to solve direct and inverse problems of optimal redundancy: (1) minimize the total cost of spare units given stock reliability requirements, and (2) maximize the stock reliability for a given total cost of spare units. The optimization is based on the steepest descent algorithm. The OSA computer model has a user-friendly interface and a convenient reporting utility. We are also able to predict approximate solution trend analytically. (C) 1999 Elsevier Science Ltd. All rights reserved.

关键词： spare allocation reliability optimization cost software tool steepest descent algorithm

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Moment method and iterative reconstruction of two-dimensional complex permittivity by using effective modes with multiple sources in the presence of noise

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RADIO SCIENCE 1996年第6期31卷 1877-1886页

作者： Park, CS Park, SK Ra, JW KOREA ADV INST SCI & TECHNOL DEPT ELECT ENGN YUSONG GU TAEJON 305701 SOUTH KOREA

An iterative hybrid algorithm combining the steepest descent algorithm of Levenberg-Marquardt and the simulated annealing algorithm is used for reconstructing the complex permittivity of a two-dimensional, high-contrast, large object. The scattered fields calculated in a cost function are expanded in angular spectral modes. The ''illposedness'' in the inversion due to the noise in the scattered fields is regularized by keeping only the effective modes and filtering out the higher angular spectral modes. The object is discretized into N square cells of unknown permittivities and N or larger number of effective modes (P) are needed for this spectral domain iterative method to reconstruct the shape and the permittivity distribution of the object. When N > P, multiple view (K) and effective modes of each view (P) make the reconstruction possible if N less than or equal to PK.

关键词： METHOD OF MOMENTS Complex permittivity Cost functions Iterative steepest descent algorithm scattered field simulated annealing algorithm

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