Description: 牛顿下山算法，给出了实例，求导数时自己把公式输入，希望有人能改变能自动求解导数，可以联系我。-Newton downhill algorithm, given examples, and derivatives of the formula when their own input, hope someone can change automatically solve the derivative, you can contact me. Platform: |
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Description: 数字图像的边缘检测
本科毕业设计（边缘检测是数字图像处理中的重要内容。本文首先对图像的边缘检测的各种算法和算子做了总结和分析。Canny最早提出了边缘检测的三条连续准则:最优检测结果、最优定位和低重复响应,并在这些准则的基础上得到了“最优线性滤波器”―高斯函数的一阶导数。经过十几年的发展,目前已经有了对这个准则的很多改进,本文也对这个方面的工作做了小结。Demigny在理论分析和实践的基础上给出了边缘检测的离散准则,并且证明在离散准则中Canny提出的第三个准则可以被阀值操作所取代。本文利用了数值方法求出了Demigny离散准则下阶梯形边缘检测的最优线性滤波器和对应着它的平滑算子。利用这个算子和Canny边缘检测方法得到了一个完整的边缘检测算法并用VC++实现了这种算法.从算法对大量图像边缘检测的结果来看,这种算法虽然简单但是效果很好,是边缘检测的一种很好的实用方法。-Edge detection is important in image procession. This paper made a summary and analysis of edge detecting algorithm and edge detector. Canny has proposed three continuous criteria to compare the performance of different filters: good detection, good localization and low-responses. Based on these criteria he got optimal filter for edge detection: derivative of Gaussian function. After more than ten years research, Canny’s theory has been ameliorated in many aspects, this paper also made a review of it. Based on the practice and theory. Demigny gave three discrete criteria for edge detection like Canny’s criteria and he has proofed that the third criterion can be replaced by an appropriate thresholding operation. This paper used numerical method to get the optimal filter and smooth operator under the Demigny’s criteria. Then I combine these filters and Canny’s edge detecting technique to get an integrated edge detecting algorithm. I have implemented the algorithm using VC++. From the res Platform: |
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Description: 求多维函数极值的一种算法，由Nelder和Mead提出，又叫单纯形算法，但和线性规划中的单纯形算法是不同的，由于未利用任何求导运算，算法比较简单，但收敛速度较慢，适合变元数不是很多的方程求极值-Multi-dimensional function extremum seeking an algorithm proposed by Nelder and Mead, also called the simplex algorithm, but in the linear programming simplex algorithm is different, because not to use any derivation operator, the algorithm is relatively simple, but slow convergence, the number of variables fit the equation is not a lot of extremal Platform: |
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Author:李军 |
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Description: Matlab数值微分的程序，包含下面所列多种微分算法。
MidPoint 中点公式求取导数
ThreePoint 三点法求函数的导数
FivePoint 五点法求函数的导数
DiffBSample 三次样条法求函数的导数
SmartDF 自适应法求函数的导数
CISimpson 辛普森数值微分法法求函数的导数-Matlab numerical differentiation procedure, including a variety of differential algorithm listed below. MidPoint the mid-point derivative formula to strike a three-point method ThreePoint derivative function for a five-point method FivePoint function derivative DiffBSample cubic spline function method of derivative adaptive method SmartDF derivative function CISimpson Simpson numerical differentiation Method derivative function Platform: |
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Author:Wade |
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Description: matlab中的数值微分，有用中点公式，自适应法，理查森外推算法等方法求函数的导数，算法的程序实现在文件中都已经给出了。-in the numerical differentiation matlab, useful midpoint formula, adaptive method, Richardson extrapolation methods such as France seek the derivative of the function, the algorithm of the program implementation in the document have been given. Platform: |
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Author:陈臻 |
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Description: 采用最常用的神经网络算法BP算法，即反向传播算法，程序涉及到梯度下降法、函数求逆及偏导数的实现数学问题-The most commonly used BP algorithm of neural network algorithm, which back propagation algorithm, the program involves gradient descent, the inverse function and the partial derivative of mathematical problems Platform: |
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Author:xiaohu |
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Description: 最优的阶梯型边缘检测算法(canny边缘检测)
1.Canny边缘检测基本原理
(1)图象边缘检测必须满足两个条件：一能有效地抑制噪声；二必须尽量精确确定边缘的位置。
(2)根据对信噪比与定位乘积进行测度，得到最优化逼近算子。这就是Canny边缘检测算子。
(3)类似与Marr（LoG）边缘检测方法，也属于先平滑后求导数的方法。
2.Canny边缘检测算法：
step1:用高斯滤波器平滑图象；
step2:用一阶偏导的有限差分来计算梯度的幅值和方向；
step3:对梯度幅值进行非极大值抑制；
step4:用双阈值算法检测和连接边缘。
step1:高斯平滑函数
-The optimal type stair edge detection algorithm (canny edge detection)
1 Canny edge detection principle
(1) the image edge detection must meet two conditions: one can effectively reduce the noise, 2 must try to accurately determine edge position.
(2) according to the signal-to-noise ratio and the product localization estimate, get optimal approximation operator. This is the Canny edge detection operators.
(3) similar to Marr (LoG) edge detection method, also belongs to the first derivative method for smooth after.
2 Canny edge detection algorithm:
Step1: using gauss filter smooth image,
Step2: a partial derivatives with finite difference to calculate gradient value and direction,
Step3: a gradient of maximum inhibition,
Step4: double threshold algorithm of edge detection and connection.
Step1: gaussian smooth functions Platform: |
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Author:lx |
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Description: 共轭梯度法是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。-Conjugate gradient method is between the steepest descent method and Newton method between a method that only use the first derivative information, but the steepest descent method to overcome the disadvantage of slow convergence, but also avoids the need to store and calculate Newton Hesse matrix and the shortcomings of the inverse, conjugate gradient method is not only linear equations to solve large-scale one of the most useful, large-scale nonlinear optimization solution is also the most efficient algorithms. Platform: |
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Author:sunling |
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Description: 共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。-Conjugate Gradient method (Conjugate Gradient) is between the steepest descent method between Newton method and a method, it only USES a derivative information, but overcome the steepest descent method slow convergence of weakness, but also avoid the Newton law needs to storage and computing Hesse inverse matrix and shortcomings, Conjugate Gradient method is not only solve linear equations with most of the large method, and also one of the most effective solution large nonlinear optimization of one of the algorithm. In all kinds of optimization algorithm, the conjugate gradient method is very important. Its advantage is the storage capacity needed, it has small step convergence, high stability, and doesn t require any exotic parameters.
Platform: |
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Author:兰中周 |
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Description: 共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数-Conjugate Gradient method (Conjugate Gradient) is between the steepest descent method between Newton method and a method, it only USES a derivative information, but overcome the steepest descent method slow convergence of weakness, but also avoid the Newton law needs to storage and computing Hesse inverse matrix and shortcomings, Conjugate Gradient method is not only solve linear equations with most of the large method, and also one of the most effective solution large nonlinear optimization of one of the algorithm. In all kinds of optimization algorithm, the conjugate gradient method is very important. Its advantage is the storage capacity needed, it has small step convergence, high stability, and doesn t require any exotic parameters numerical experiment, this is the modern scientific computing of the answer above problem sets Platform: |
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Author:兰中周 |
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Description: 共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。-Conjugate gradient method (Conjugate Gradient) between the steepest descent between law and Newton' s method is a method, it is only the first derivative information, but to overcome the steepest descent method of slow convergence shortcomings, but also avoid the Newton method needs to be stored and calculate the Hesse matrix and the inverse of the shortcomings of the conjugate gradient method is not only the most useful way to solve the large linear equations, one is also the solution of large-scale nonlinear optimization one of the most effective algorithm. Platform: |
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Description: 利用Matlab内建的快速傅氏变换函数可以方便地在波数域计算重磁异常导数。介绍了基于Matlab语言的波数域求导的算法，给出了程序源代码，讨论了一些有助于提高计算精度的编程技巧。通过模型试验和数据分析，
发现在计算垂向导数时波数域求导算法的精度比傅氏级数的精度有明显改善；而水平导数的计算，2种方法的精度相当。在某区钾盐勘探中，用该方法处理高精度重力剖面数据，取得了较好效果。-It is convenient to calculate derivative in wave number space using the inbuih F胛function in Matlab．This paper describes
a matlab algorithm for derivative calculation of 1 D gravity and magnetic anomaly in wave number space，gives code of program and
deals with some programming skills for precision improvement．Throngh model test and data analysis，it is found that the precision of
the F盯method is much higher than that of the Fourier Series method in vertical derivative calculation．In horizontal derivative calculation，
however，the precisions of the two methods ale almost the same．During kainite exploration in a certain basin，satisfactory result
Wag obtained in the processing of gravity profile data using this method． Platform: |
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Description: Levenberg-Marquardt算法是最优化算法中的一种。最优化是寻找使得函数值最小的参数向量。根据求导数的方法.-Levenberg-Marquardt algorithm is an optimization algorithm. Makes optimization is to find the minimum value of the parameter vector function. Method according to the number of derivative. Platform: |
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Author:赵宇 |
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Description: powell算法设计
鲍威尔法又称方向加速法，它由Powell于1964年提出，是利用共轭方向可以加快收敛速度的性质形成的一种搜索方法。该方法不需要对目标函数进行求导，当目标函数的导数不连续的时候也能应用，因此，鲍威尔算法是一种十分有效的直接搜索法。
Powell法可用于求解一般无约束优化问题，对于维数n<20的目标函数求优化问题，此法可获得较满意的结果。
不同于其他的直接法，Powell法有一套完整的理论体系，故其计算效率高于其他直接法。该方法使用一维搜索，而不是跳跃的探测步。同时，Powell法的搜索方向不一定为下降方向。(Powell method can be used to solve general unconstrained optimization problems. For the optimization of dimension n<20 objective function, this method can obtain satisfactory results.
Unlike other direct methods, the Powell method has a complete set of theoretical systems, so its computational efficiency is higher than other direct methods. The method uses one-dimensional search instead of jumping detection steps. At the same time, the search direction of the Powell method is not necessarily for the downward direction.) Platform: |
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