Within this book the fundamental concepts associated with the topic of power electronic control are covered alongside the latest equipment and devices, new application areas and associated computer-assisted methods. *A practical guide to the control of reactive power systems *Ideal for postgraduate and professional courses *Covers the latest equipment and computer-aided analysis
標(biāo)簽： power electronic electrical system
上傳時間： 2015-02-20
上傳用戶：12345654321
TPMath is a library of scientific programs written in Pascal. Available in several versions according to the compiler, it is proposed as an alternative to the famous Numerical Recipes, for which the Pascal version is no longer developed, or to the Borland Numerical methods Toolbox which is no longer available.
上傳時間： 2015-03-06
上傳用戶：y_flin
Collection of key-value pairs. TDictionary represents a generic collection of key-value pairs. This class provides a mapping from a collection of keys to a collection of values. When you create a TDictionary object, you can specify various combinations of initial capacity, equality operation, and initial content. You can add a key that is associated with a corresponding value with the Add or AddOrSetValue methods. You can remove entries with Remove or Clear, which removes all key-value pairs. Adding or removing a key-value pair and looking up a key are efficient, close to O(1), because keys are hashed. A key must not be nil (though a value may be nil) and there must be an equality comparison operation for keys. You can test for the presence or keys and values with the TryGetValue, ContainsKey and ContainsValue methods. The Items property lists all Count dictionary entries. You can also set and get values by indexing the Items property. Setting the value this way overwrites any existing value. The class TObjectDictionary inherits from TDictionary and provides an automatic mechanism for freeing objects removed from dictionary entries.
標(biāo)簽： Delphi 泛型
上傳時間： 2015-07-01
上傳用戶：mirage
matlab有限元網(wǎng)格劃分程序 DistMesh is a simple MATLAB code for generation of unstructured triangular and tetrahedral meshes. It was developed by Per-Olof Persson (now at UC Berkeley) and Gilbert Strang in the Department of Mathematics at MIT. A detailed description of the program is provided in our SIAM Review paper, see documentation below. One reason that the code is short and simple is that the geometries are specified by Signed Distance Functions. These give the shortest distance from any point in space to the boundary of the domain. The sign is negative inside the region and positive outside. A simple example is the unit circle in 2-D, which has the distance function d=r-1, where r is the distance from the origin. For more complicated geometries the distance function can be computed by interpolation between values on a grid, a common representation for level set methods. For the actual mesh generation, DistMesh uses the Delaunay triangulation routine in MATLAB and tries to optimize the node locations by a force-based smoothing procedure. The topology is regularly updated by Delaunay. The boundary points are only allowed to move tangentially to the boundary by projections using the distance function. This iterative procedure typically results in very well-shaped meshes. Our aim with this code is simplicity, so that everyone can understand the code and modify it according to their needs. The code is not entirely robust (that is, it might not terminate and return a well-shaped mesh), and it is relatively slow. However, our current research shows that these issues can be resolved in an optimized C++ code, and we believe our simple MATLAB code is important for demonstration of the underlying principles. To use the code, simply download it from below and run it from MATLAB. For a quick demonstration, type "meshdemo2d" or "meshdemond". For more details see the documentation.
標(biāo)簽： matlab有限元網(wǎng)格劃分程序
上傳時間： 2015-08-12
上傳用戶：凜風(fēng)拂衣袖
Computational models are commonly used in engineering design and scientific discovery activities for simulating complex physical systems in disciplines such as fluid mechanics, structural dynamics, heat transfer, nonlinear structural mechanics, shock physics, and many others. These simulators can be an enormous aid to engineers who want to develop an understanding and/or predictive capability for complex behaviors typically observed in the corresponding physical systems. Simulators often serve as virtual prototypes, where a set of predefined system parameters, such as size or location dimensions and material properties, are adjusted to improve the performance of a system, as defined by one or more system performance objectives. Such optimization or tuning of the virtual prototype requires executing the simulator, evaluating performance objective(s), and adjusting the system parameters in an iterative, automated, and directed way. System performance objectives can be formulated, for example, to minimize weight, cost, or defects; to limit a critical temperature, stress, or vibration response; or to maximize performance, reliability, throughput, agility, or design robustness. In addition, one would often like to design computer experiments, run parameter studies, or perform uncertainty quantification (UQ). These approaches reveal how system performance changes as a design or uncertain input variable changes. Sampling methods are often used in uncertainty quantification to calculate a distribution on system performance measures, and to understand which uncertain inputs contribute most to the variance of the outputs. A primary goal for Dakota development is to provide engineers and other disciplinary scientists with a systematic and rapid means to obtain improved or optimal designs or understand sensitivity or uncertainty using simulationbased models. These capabilities generally lead to improved designs and system performance in earlier design stages, alleviating dependence on physical prototypes and testing, shortening design cycles, and reducing product development costs. In addition to providing this practical environment for answering system performance questions, the Dakota toolkit provides an extensible platform for the research and rapid prototyping of customized methods and meta-algorithms
標(biāo)簽： Optimization and Uncertainty Quantification
上傳時間： 2016-04-08
上傳用戶：huhu123456
一本講述求解稀疏線性方程的迭代方法的外文書，閱讀需要具有較強(qiáng)的英語能力
標(biāo)簽： Iterative methods Systems Linear Sparse
上傳時間： 2016-05-21
上傳用戶：通行天下
caculation,method,gold,optimazation theory and methods，matlab
標(biāo)簽： caculation method gold optimazation
上傳時間： 2016-12-22
上傳用戶：楊一一一
Reconstruction- and example-based super-resolution (SR) methods are promising for restoring a high-resolution (HR) image from low-resolution (LR) image(s). Under large magnification, reconstruction-based methods usually fail to hallucinate visual details while example-based methods sometimes introduce unexpected details. Given a generic LR image, to reconstruct a photo-realistic SR image and to suppress artifacts in the reconstructed SR image, we introduce a multi-scale dictionary to a novel SR method that simultaneously integrates local and non-local priors. The local prior suppresses artifacts by using steering kernel regression to predict the target pixel from a small local area. The non-local prior enriches visual details by taking a weighted average of a large neighborhood as an estimate of the target pixel. Essentially, these two priors are complementary to each other. Experimental results demonstrate that the proposed method can produce high quality SR recovery both quantitatively and perceptually.
標(biāo)簽： Super-resolution Multi-scale Dictionary Single Image for
上傳時間： 2019-03-28
上傳用戶：fullout
Accurate pose estimation plays an important role in solution of simultaneous localization and mapping (SLAM) problem, required for many robotic applications. This paper presents a new approach called R-SLAM, primarily to overcome systematic and non-systematic odometry errors which are generally caused by uneven floors, unexpected objects on the floor or wheel-slippage due to skidding or fast turns.The hybrid approach presented here combines the strengths of feature based and grid based methods to produce globally consistent high resolution maps within various types of environments.
標(biāo)簽： localization environments challenging Resilient mapping R-SLAM and in
上傳時間： 2019-09-15
上傳用戶：zhudx2007
Bulletin of the American Mathematical Society Volume 49 issue 1 1943 [doi 10.1090_s0002-9904-1943-07818-4] Courant, R. -- Variational methods for the solution of problems of equilibrium and vibratio
上傳時間： 2020-05-10
上傳用戶：藍(lán)天自由
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