FORTRAN

rls algorithm applied to adaptive beamforming in smart antennas in circular arrys

利用全通滤波器的原理对于因信号进行改变相位，嵌入数字水印(use of the all-pass filter principle as a result of changes in signal phase, embedded digital watermarking)

This package is performing the K-medoids clustering algorithm on any data.

目录 1.图像反转 2 2.灰度线性变换 2 3.非线性变换 4 4.直方图均衡化 5 5. 线性平滑滤波器 6 6.中值滤波器 7 7.用Sobel算子和拉普拉斯对图像锐化： 8 8.梯度算子检测边缘 9 9.LOG算子检测边缘 11 10.Canny算子检测边 缘 12 11.边界跟踪 （bwtraceboundary函数） 13 12.Hough变换 14 13.直方图阈值法 16 14. 自动阈值法：Otsu法 18 15.膨胀操作 19 16.腐蚀操作 20 17.开启和闭合操作 21 18.开启和闭合组合操作 22 19.形态学边界提取 24 20.形态学骨架提取 25 21.直接提取四个顶点坐标 26 22.文件打开窗口 27 (Contents 1 image reversal 22 23 gray linear transformation. Nonlinear transformation 44. Histogram equalization 55 linear smoothing filters 66. Median filter 77. Sobel operator and Rapp Las Image Sharpening: 88. gradient edge detection operator 9 9.LOG edge detection operator 11 10.Canny count of edge detection 1211. the border tracking (bwtraceboundary function) 1413 13 12.Hough transform histogram. threshold Law 1614 automatic thresholding method: Otsu 1815 expansion operation 1916. corrosion operation 2017. opening and closing operation of 2118. combination of opening and closing operation 2219. morphology boundary extraction 24 20 morphological skeleton extraction 2521 direct extraction of four vertex coordinates 2622 File Open window 27)

说明：  matlab三维回旋仿真 使用了S函数，仿真时间300s，对于初学者有一定帮助(Matlab 3D gyration simulation uses s function)

说明：  关于基于梯度归一化的模型参考自适应的一个m文件(Gradient-based normalization on the model reference adaptive file a m)

sigital signal processing programs for electronics

基追踪算法，通用程序，稀疏性恢复、压缩感知两大算法之一(Base tracking algorithm, common procedures, sparsity recovery, one of the two compression algorithms perception)

细化骨架的简单程序，对二值图进行操作，如果对于空洞比较大的，先进行膨胀操作(Refinement of skeleton simple program, if the hole bigger, to expand operations )

说明：  蚁群算法是模拟蚁群觅食行为的一种优化算法。在整个觅食过程中蚂蚁散播信息素，蚂蚁通过感知到的信息素多少，来决定所要选择的下一个栅格。蚁群算法的核心部分在于模拟了蚁群的转移概率选择行为，通过使用信息素和启发式函数值进行转移概率计算。粒子群算法可以用于机器人运动轨迹规划，求得最短路径(Ant colony algorithm is an optimization algorithm to simulate foraging behavior of ant colony.The ant disperses pheromones throughout the foraging process. The ant senses how many pheromones it has to choose the next grid.The core part of ant colony algorithm is to simulate the transfer probability selection behavior of ant colony and calculate the transfer probability by using pheromones and heuristic function values.Particle swarm optimization (pso) can be used for robot trajectory planning to obtain the shortest path)