tdpsolamatlab

简单的数字图像处理程序，对新手很有帮助，内含很多简易程序(Digital image processing procedures)

matlab/C++ 源代码，在数字相关技术中应用非常高效准确。(matlab/C++ source code in digital image correlation. It s very useful and convenient)

基于电压源换流器的有源电力滤波器APF和静止无功发生器SVG的PSIM仿真模型(PSIM simulation model of APF and SVG based on voltage source converter)

This pdf file is about gabor deconvolution.

SVM method is used for image processing

图论算法matlab实现，图的连通性计算算法(Graph theory algorithm matlab implementation, the connectivity map computation algorithm)

计算流体力学的网格划分，这是计算流体力学的基础(The computational fluid dynamics, this is the meshing computational fluid dynamics)

The toolbox contains functions to estimate and simulate multivariate copula GARCH models and Copula Vines. Supported copulas are the Gaussian and the T Copula. For the dynamic correlations, various specifications are supported.

1 SIFT 发展历程 SIFT算法由D.G.Lowe 1999年提出，2004年完善总结。后来Y.Ke将其描述子部分用PCA代替直方图的方式，对其进行改进。 2 SIFT 主要思想 SIFT算法是一种提取局部特征的算法，在尺度空间寻找极值点，提取位置，尺度，旋转不变量。 3 SIFT算法的主要特点： a) SIFT特征是图像的局部特征，其对旋转、尺度缩放、亮度变化保持不变性，对视角变化、仿射变换、噪声也保持一定程度的稳定性。 b) 独特性(Distinctiveness)好，信息量丰富，适用于在海量特征数据库中进行快速、准确的匹配[23]。 c) 多量性，即使少数的几个物体也可以产生大量SIFT特征向量。 d) 高速性，经优化的SIFT匹配算法甚至可以达到实时的要求。 e) 可扩展性，可以很方便的与其他形式的特征向量进行联合。 4 SIFT算法步骤： 1） 检测尺度空间极值点 2） 精确定位极值点 3） 为每个关键点指定方向参数 4） 关键点描述子的生成 本包内容为sift算法matlab源码(1 SIFT course of development SIFT algorithm by DGLowe in 1999, the perfect summary of 2004. Later Y.Ke its description of the sub-part of the histogram with PCA instead of its improvement. 2 the SIFT main idea The SIFT algorithm is an algorithm to extract local features in scale space to find the extreme point of the extraction location, scale, rotation invariant. 3 the main features of the SIFT algorithm: a) SIFT feature is the local characteristics of the image, zoom, rotate, scale, brightness change to maintain invariance, the perspective changes, affine transformation, the noise also maintain a certain degree of stability. b) unique (Distinctiveness), informative, and mass characteristics database for fast, accurate matching [23]. c) large amounts, even if a handful of objects can also produce a large number of SIFT feature vectors. d) high-speed and optimized SIFT matching algorithm can even achieve real-time requirements. e) The scalability can be very convenient fe)

LEACH 基本演算法，使用MATLAB(LEACH basic algorithms using MATLAB)