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nonlinear algorithms in isogram extraction from topographic maps

Conference on nonlinear Image Processing IX

作者： Lukin, VV Ponomarenko, NN Kurekin, AA Zelensky, AA Astola, JT Koivisto, PT Saarinen, KP Kharkov Aviat Inst Dept 507 UA-310070 Kharkov Ukraine

ISBN: (纸本)0819427446

A method for isogram extraction from topographic maps is proposed and analyzed. Main part of the extraction is done using automatic software based on nonlinear algorithms. Possibly needed final corrections are done in an interactive mode. Iterative procedures are used both to provide reliability and to minimize the number of operations performed by the user in the interactive mode. Illustrations are presented to clarify the operations, goals and obtained results. Also, techniques for relief recovery are proposed and their accuracy is studied.

关键词： topographic maps semiautomatic isogram extraction relief recovery nonlinear algorithms

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Kalman filtering with state constraints: a survey of linear and nonlinear algorithms

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IET CONTROL THEORY AND APPLICATIONS 2010年第8期4卷 1303-1318页

作者： Simon, D. Cleveland State Univ Dept Elect & Comp Engn Cleveland OH 44115 USA

The Kalman filter is the minimum-variance state estimator for linear dynamic systems with Gaussian noise. Even if the noise is non-Gaussian, the Kalman filter is the best linear estimator. For nonlinear systems it is not possible, in general, to derive the optimal state estimator in closed form, but various modifications of the Kalman filter can be used to estimate the state. These modifications include the extended Kalman filter, the unscented Kalman filter, and the particle filter. Although the Kalman filter and its modifications are powerful tools for state estimation, we might have information about a system that the Kalman filter does not incorporate. For example, we may know that the states satisfy equality or inequality constraints. In this case we can modify the Kalman filter to exploit this additional information and get better filtering performance than the Kalman filter provides. This paper provides an overview of various ways to incorporate state constraints in the Kalman filter and its nonlinear modifications. If both the system and state constraints are linear, then all of these different approaches result in the same state estimate, which is the optimal constrained linear state estimate. If either the system or constraints are nonlinear, then constrained filtering is, in general, not optimal, and different approaches give different results.

关键词： Signal processing theory extended Kalman filter optimal constrained linear state estimate constraint theory nonlinear algorithms Other topics in statistics linear dynamic systems state estimation minimum variance state estimator Gaussian noise state constraints Kalman filters Filtering methods in signal processing optimal state estimator unscented Kalman filter

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Fast approximate statistical nonlinear algorithms for diffusion optical tomography of objects with a complicated internal structure

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QUANTUM ELECTRONICS 2001年第12期31卷 1095-1100页

作者： Tret'yakov, EV Shuvalov, VV Shutov, IV Moscow MV Lomonosov State Univ Int Teaching & Res Laser Ctr Moscow 119899 Russia

Fast approximate statistical nonlinear algorithms (capable of real-time operation) for solving direct and inverse problems in the diffusion optical tomography are described. These algorithms were tested by reconstructing a rather complicated internal structure (containing up to three strongly absorbing inclusions no smaller than 5 turn in size) of strongly scattering and weakly absorbing large (up to 140 mm) model objects (with scattering and absorption coefficients equal to 1.4 and 0.005-0.015 mm(-1) respectively). Experiments were performed using cw radiation of low-power diode lasers (with input power below 20 mW) in the near IR range (between 770 and 820 mn).

关键词： optical tomography nonlinear algorithms statistics

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Comparison and Analysis of nonlinear algorithms for Compressed Sensing in MRI

Comparison and Analysis of Nonlinear Algorithms for Compress...

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32nd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBC 10)

作者： Yu, Yeyang Hong, Mingjian Liu, Feng Wang, Hua Crozier, Stuart Univ Queensland Sch Informat Technol & Elect Engn Brisbane Qld Australia Chongqing Univ Sch Software Engn Chongqing 630044 Peoples R China

ISBN: (纸本)9781424441242

Compressed sensing (CS) theory has been recently applied in Magnetic Resonance Imaging (MRI) to accelerate the overall imaging process. In the CS implementation, various algorithms have been used to solve the nonlinear equation system for better image quality and reconstruction speed. However, there are no explicit criteria for an optimal CS algorithm selection in the practical MRI application. A systematic and comparative study of those commonly used algorithms is therefore essential for the implementation of CS in MRI. In this work, three typical algorithms, namely, the Gradient Projection For Sparse Reconstruction (GPSR) algorithm, Interior-point algorithm (l(1)_ls), and the Stagewise Orthogonal Matching Pursuit (StOMP) algorithm are compared and investigated in three different imaging scenarios, brain, angiogram and phantom imaging. The algorithms' performances are characterized in terms of image quality and reconstruction speed. The theoretical results show that the performance of the CS algorithms is case sensitive;overall, the StOMP algorithm offers the best solution in imaging quality, while the GPSR algorithm is the most efficient one among the three methods. In the next step, the algorithm performances and characteristics will be experimentally explored. It is hoped that this research will further support the applications of CS in MRI.

关键词： GPSR algorithm StOMP algorithm biomedical MRI biomedical MRI compressed sensing implementation data compression gradient projection for sparse reconstruction image quality image reconstruction image reconstruction speed interior-point algorithm iterative methods magnetic resonance imaging medical image processing nonlinear algorithms nonlinear equation system nonlinear equations stagewise orthogonal matching pursuit

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Comments on "Distributed nonlinear control algorithms for network consensus" [Automatica 44 (2008) 2375-2381]

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AUTOMATICA 2010年第9期46卷 1568-1568页

作者： Liu, Xiwei Fudan Univ Key Lab Nonlinear Sci Chinese Minist Educ Sch Math Shanghai 200433 Peoples R China

关键词： Consensus nonlinear algorithms

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BLIND SEPARATION OF SOURCES - A nonlinear NEURAL ALGORITHM

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NEURAL NETWORKS 1992年第6期5卷 937-947页

作者： BUREL, G Thomson-CSF Laboratoires Electroniques de Rennes France

In many signal processing applications, the signals provided by the sensors are mixtures of many sources, The problem of separation of sources is to extract the original signals from these mixtures. A new algorithm, based on ideas of back propagation learning, is proposed for source separation. No a priori information on the sources themselves is required, and the algorithm can deal even with nonlinear mixtures. After a short overview of previous works in that field, we will describe the proposed algorithm, then some experimental results will be discussed.

关键词： SEPARATION OF SOURCES HIGH ORDER MOMENTS MIXTURE OF SOURCES nonlinear algorithms INDEPENDENT COMPONENT ANALYSIS NEURAL NETWORKS BACK PROPAGATION

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A new method for periodic solutions of nonlinear eddy current problems

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IEEE TRANSACTIONS ON MAGNETICS 1999年第3期35卷 1115-1118页

作者： Weymann, J Thomas, P Gaombalet, J Elect France Direct Etud & Rech F-92141 Clamart France

A new algorithm for the computation of steady-state conditions of electric machines is presented, It is based on a large time increment method used in mechanics, It is applied to the electromagnetic field computation ... 详细信息

关键词： nonlinear algorithms Maxwell equations eddy currents nonlinear magnetics generators

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An embedded 3(2) pair of nonlinear methods for solving first order initial-value ordinary differential systems

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NUMERICAL algorithms 2017年第3期75卷 509-529页

作者： Ramos, Higinio Singh, Gurjinder Kanwar, V. Bhatia, Saurabh Univ Salamanca Sci Comp Grp Plaza Merced E-37008 Salamanca Spain Escuela Politecn Super Zamora Campus Viriato Zamora 49022 Spain Panjab Univ Univ Inst Engn & Technol Chandigarh 160014 India

In this paper, we present two families of second-order and third-order explicit methods for numerical integration of initial-value problems of ordinary differential equations. Firstly, a family of second-order methods with two free parameters is derived by considering a suitable rational approximation to the theoretical solution of the problem at some grid points. Imposing that the principal term of the local truncation error of this family vanishes, we obtain an expression for one of the parameters in terms of the other. With this approach, a new one-parameter family of third-order methods is obtained. By selecting any 3(2) pair of second and third order methods, they can be implemented as an embedded type method, thus leading to a variable step-size formulation. We have considered one 3(2) pair of second and third order methods and made a comparison of numerical results with several ode solvers which are currently used in practice. The comparison of numerical results shows that the embedded 3(2) pair outperforms the methods considered for comparison.

关键词： nonlinear algorithms Ordinary differential equations Initial-value problems Rational approximations A-stability

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A nonlinear MINIMAX ALLOCATION PROBLEM WITH MULTIPLE KNAPSACK CONSTRAINTS

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OPERATIONS RESEARCH LETTERS 1991年第4期10卷 183-187页

作者： LUSS, H AT&T BELL LABS HOLMDELNJ 07733 USA

We consider a nonlinear minimax allocation problem with multiple knapsack-type resource constraints. Each term in the objective function is a nonlinear, strictly decreasing and continuous function of a single variable. All variables are continuous and nonnegative. A previous algorithm for such problem repeatedly solves relaxed problems without the nonnegativity constraints. That algorithm is particularly efficient for certain nonlinear functions for which there are closed-form solutions for the relaxed problems;for other functions, however, the algorithm must employ search methods. We present a new algorithm that uses at each iteration simple-to-compute algebriac expressions to check optimality conditions, instead of solving the relaxed minimax problems. The new algorithm is therefore significantly more efficient for more general nonlinear functions.

关键词： RESOURCE ALLOCATION LARGE-SCALE SYSTEMS nonlinear algorithms PRODUCTION PLANNING

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A Parallel Python library for nonlinear systems

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JOURNAL OF SUPERCOMPUTING 2011年第3期58卷 438-448页

作者： Migallon, Hector Migallon, Violeta Penades, Jose Univ Miguel Hernandez Dept Fis & Arquitectura Comp Alicante 03202 Spain Univ Alicante Dept Ciencia Comp & Inteligencia Artificial Alicante 03071 Spain

In this paper, we present PyPANCG, a Python library-interface that implements both the conjugate gradient method and the preconditioned conjugate gradient method for solving nonlinear systems. We describe the use of the library and its advantages in order to get fast development. The aim of this library is to develop high performance scientific codes for high-end computers hiding many of the underlying low-level programming complexities from users with the use of a high-level Python interface. The library has been designed for adapting to different stages of the design process, depending on whether the purpose is computational performance or fast development. Experimental results report the performance of our approach on different parallel computers.

关键词： Parallel libraries nonlinear algorithms Python high-level interfaces

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