fangchengzudiedaifa

最新的libSVM3.0版本，台湾林智仁团队编写的。(The newest version of livsvm toolbox)

CN103778102A基于干扰噪声矩阵重构的自适应波束形成方法(CN103778102A interference noise matrix remodeling based on adaptive beamforming method)

通过读取GPS RINEX格式观测和星历文件，实现了GPS伪距单点定位，经过数据验证，该算法定位结果有效。(By reading the GPS RINEX format observation and ephemeris file, the GPS pseudorange single point positioning is realized, and the positioning result is valid through data verification.)

使用MATLAB软件将三维图转化为二维图形实现。(Using the MATLAB software to three-dimensional images into two-dimensional graphics to achieve.)

用于测量随机散射介质光学传输矩阵TM 直接运行主函数即可 注意相机型号：MT9F002 SLM型号：RL-SLM-R2(Used to measure the transmission matrix of random scatter medium(TM).Run the main directly camear:MT9F002 SLM:RL-SLM-R2)

c++程序设计讲义 cppprograming 含源码(c++ programming including lectures cppprograming source)

A Sparse Signal Reconstruction Perspective for Source Localization With Sensor Arrays Dmitry Malioutov, Student Member, IEEE, Müjdat Ç etin, Member, IEEE, and Alan S. Willsky, Fellow, IEEE

直方图均衡化，数字图像处理，简单matlab函数(Histogram equalization, digital image processing, a simple matlab function)

说明：  基本的粒子滤波算法，所用数值模型为带控制量的非线性模型，可修改噪声类型，并可和EKF相比较(Basic particle filter algorithm for the numerical model used to control the volume with the non-linear model, can modify the type of noise can be compared and the EKF)

实现9/7小波正反变换 注1： 采用标准正交方法，对行列采用不同矩阵（和matlab里不同） 注2： 为了保证正交，所有边界处理，全部采用循环处理 注3： 正交性验证，将单位阵带入函数，输出仍是单位阵（matlab不具有此性质） 注4： 此程序是矩阵实现，所以图像水平分量和垂直分量估计被交换位置 注5： 此程序实现的是类小波（wavelet-like）变换，是介于小波包变换与小波变换之间的变换 注6： 此程序每层变换相对原图像矩阵，产生的矩阵都是正交阵，这和小波包一致 注7： 但小波变换每层产生的矩阵，是相对每个待分解子块的正交矩阵，而不是原图像的正交矩阵 注8： 且小波变换产生的正交矩阵维数，随分解层数2分减少 注9: 提升系数可以在MATLAB7.0以上版本，用liftwave( 9.7 )获取，这里直接给出，考虑兼容性 注10：由于MATLAB数组下标从1开始，所以注意奇偶序列的变化 注11：d为对偶上升，即预测；p为原上升，即更新(Note 1: The standard orthogonal method, the ranks of the different matrices (and matlab where different) Note 2: In order to ensure orthogonality, all boundary treatment, all with recycling Note 3: Orthogonal validation, the identity matrix into the function, the output is still the unit matrix (matlab does not have this property) Note 4: This program is a matrix to achieve, so the image horizontal and vertical components is estimated to be swapped Note 5: This class implements the wavelet (wavelet-like) transformation, is between the wavelet packet transform and wavelet transform between Note 6: This procedure transforms each image relative to the original matrix, the resulting matrix are orthogonal matrix, consistent with this and wavelet packet Note 7: But each generation wavelet transform matrix, is to be broken down for each sub-block relative to the orthogonal matrix, rather than the original image of the orthogonal matrix Note 8: Wavelet transf)