MatlabExpand-programming

BOOST库导论，介绍了BOOST库中一些重要的库。(Introduction BOOST library, the library introduced a number of important BOOST library.)

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)

两倍过采样的频域均衡器，采用MMSE算法最小化均方误差(two upsample frequency decision feedback equaliter，with MMSE criterion)

自适应LMS盲均衡算法，在MATLAB下实现，比较简单(err)

The following fuzzy modeling exercises run in the MATLAB environment. The interaction required by the user is guided by instructions and editable fields menus. The user can change various parameters of a system, and execute modeling commands to verify the resulting system. In some exercises, it is also possible to manually edit the fuzzy system initially generated with the parameters given by the user, in order to enhance and fine tune the performance of the model.

说明：  经过调试过的朴素贝叶斯分类器，可以正常使用。(After debugging through the Naive Bayes classifier, can be used normally . )

Introduction to GUIDE in matlab

基于机器学习->增强型学习的路径规划算法实现，包括Q学习和动态学习。(Implementation of Reinforced Learning Algrithm for grid path planning problem, including Q-learning and Dynamic Learning.)

说明：  MATLAB2019官方入门文档，详细介绍了MATLAB2019的使用方法与技巧(The official entry document of matlab2019 introduces the use methods and skills of matlab2019 in detail.)

cdma code for wireless communication