matlab

matlab实现的频率空间转换，含完整实验报告(matlab implementation of the frequency space conversion, including a full lab report)

说明：  经典相机标定法，张正友标定法的MATLAB实现，值得借鉴(The classical camera calibration method, zhang zhengyou calibration method MATLAB implementation, it is worth learning)

在matlab中计算灰色关联度,可以计算农业经济，人文生态，环境，等等，用途广泛，方便使用。(gray system is good，many people liked it,it can calculate many things for agriculture,econmics and other things.so try to download it and use it.)

英文资料。关于机器人视觉伺服的全面综述。有参考价值。(English. Servo robot vision of the comprehensive overview. Reference value.)

经典算法的实现，爬山算法。适合初学matlab和学习经典算法的学者下载学习。(Classic algorithm, hill-climbing algorithm. Suitable for beginners of Matlab and learning classical algorithm scholars Download learning.)

程序代码说明 P0401：用Prewitt算子检测图像的边缘 P0402：用不同σ值的LoG算子检测图像的边缘 P0403：用Canny算子检测图像的边缘 P0404：图像的阈值分割 P0405：用水线阈值法分割图像 P0406：对矩阵进行四叉树分解 P0407：将图像分为文字和非文字的两个类别 P0408：形态学梯度检测二值图像的边缘 P0409：形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象(Procedure Code Description P0401: detection using Prewitt operator Edge P0402: σ values with different operator LoG edge detection image P0403: detection using Canny operator Edge P0404: Image Thresholding P0405: thresholds for water line image segmentation method P0406: for the matrix decomposition quadtree P0407: text and images are divided into two categories of non-text P0408: detection of morphological gradient of the edge binary image P0409: morphological examples- from the PCB to remove all images current lines, retaining only the target chip)

周期图法计算在白噪声环境下的正弦信号功率谱密度(Periodogram method under the white noise power spectral density of the sinusoidal signal)

PID 控制 应用 程序chap1_.mdl；chap3.mdl；chap3.mdl；chap6.mdl；chap6.md(PID control)

导入RAW格式的原始图像数据，并在Matlab的Figure界面中显示图像。适用于将获得的CCD相机原始图像保存后的数据分析与计算(Import the*.raw original image data and display it on the interface of "Figure" in Matlab. This function is applied to analize and caculate the original CCD image data)

Implements Maximum likelihood estimation of beta and other parameters for model of stock portfolio vs. index using kalman filter