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adapQuad
迭代自适应Simpson，Lobatto积分
In almost every standard book on numerics quadrature algorithms like the adaptive Simpson or the adaptive Lobatto algorithm are presented in a recursive way. The benefit of the recursive programming is the compact and clear representation. However, recursive quadrature algorithms might be transformed into iterative quadrature algorithms without major modifications in the structure of the algorithm.
We present iterative adaptive quadrature algorithm (adaptiveSimpson and adaptiveLobatto), which preserves the compactness and the clarity of the recursive algorithms (e.g. quad, quadv, and quadl). Our iterative algorithm provides a parallel calculation of the integration function, which leads to tremendous gain in run-time, in general. Our results suggest a general iterative and not a recursive implementation of adaptive quadrature formulas, once the programming language permits parallel access to the integration function. For details the attached PDF file Conrad_08.pdf. (Iterative Adaptive Simpson, Lobatto Points In almost every standard book on numerics quadrature algorithms like the adaptive Simpson or the adaptive Lobatto algorithm are presented in a recursive way. The benefit of the recursive programming is the compact and clear representation. However, recursive quadrature algorithms might be transformed into iterative quadrature algorithms without major modifications in the structure of the algorithm.We present iterative adaptive quadrature algorithm (adaptiveSimpson and adaptiveLobatto), which preserves the compactness and the clarity of the recursive algorithms (eg quad, quadv, and quadl) . Our iterative algorithm provides a parallel calculation of the integration function, which leads to tremendous gain in run-time, in general. Our results suggest a general iterative and not a recursive implementation of adaptive quadrature formulas, once the programming language permits parallel access to the integration function. For details the attached PDF file Conrad_08.pdf.)
- 2008-08-14 22:44:04下载
- 积分：1
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MATLAByuyanjichu03
matlab 入门基础知识，数字图像处理系列入门教材系列之一(Basic knowledge of introduction to matlab, digital image processing one of series of introductory textbook series)
- 2013-11-13 00:04:11下载
- 积分：1
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异步双馈风力发电机的simulink仿真模型DFIG2
异步双馈风力发电机的simulink仿真模型，可修改参数(Simulink simulation model of asynchronous doubly-fed wind turbines, can modify the parameters)
- 2020-07-05 18:58:59下载
- 积分：1
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WOA算法
说明： 鲸鱼优化算法(WOA)也是一种元启发式优化算法。一种新的模拟座头鲸狩猎行为的元启发式优化算法(鲸鱼优化算法，WOA)。目前的工作与其他群优化算法相比的主要区别在于，采用随机或最佳搜索代理来模拟捕猎行为，并使用螺旋来模拟座头鲸的泡泡网攻击机制。(Whale optimization algorithm (WOA) is also a meta heuristic optimization algorithm. A new meta heuristic optimization algorithm (whale optimization algorithm, WOA) is proposed to simulate the hunting behavior of humpback whales. The main difference between the current work and other swarm optimization algorithms is that the random or optimal search agent is used to simulate the hunting behavior, and the spiral is used to simulate the bubble net attack mechanism of humpback whales)
- 2020-10-11 17:51:06下载
- 积分：1
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PatternRecognition
模式识别各种算法简单介绍，程序简单，容易理解(Brief introduction to a variety of pattern recognition algorithms, the program is simple, easy to understand)
- 2010-12-01 09:24:45下载
- 积分：1
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radon_transform
该算法主要是利用randon变换实现直线，椭圆，抛物线等规则曲线的自动提取(The algorithm is the main randon transformation to realize the straight line, elliptic, parabolic curve and rules of the automatic extraction
)
- 2012-04-22 18:34:42下载
- 积分：1
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SurveyTextMining
这是一本关于文本挖掘的书籍，包括聚类 分类 信息提取的内容(This is a book on text mining, including clustering classification of the content of information extraction)
- 2007-08-27 18:41:25下载
- 积分：1
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vh
说明： LMS自适应算法的matlab仿真源程序(LMS adaptive algorithm matlab simulation source)
- 2009-05-07 21:34:54下载
- 积分：1
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Code_GK
Matlab code for GK Algorithm for segmentation
- 2015-04-14 15:44:29下载
- 积分：1
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Bayesianmethods
本压缩文件详细介绍了Robert Piche博士关于贝叶斯算法的理论和他的笔记，其中文档中还包含源码程序，另附两个m文件源程序，是一个非常实用的学习及参考资料(In this course we present the basic principles of Bayesian statistics (an alternative to "orthodox" statistics). We start by learning how to estimate parameters for standard models (normal, binomial, Poisson) and then get acquainted with computational methods (MCMC) and software (WinBUGS) that can solve complicated problems that arise in real applications. Advanced topics include model comparison and decision theory. )
- 2009-10-18 10:58:52下载
- 积分：1
