weiqinglaieg2_1

其中给出了多种调制方式的调制及解调程序，对初学者有一定帮助。(Which gives a wide range of modulation of the modulation and demodulation process, has a certain extent, help for beginners.)

一部很经典的关于MATLAB的教材，内容很详细，不多说了，自己下载吧！(this is very good book,if you now study MATLAB,you must load it.)

这是一个正交交叉的量子行为粒子群算法的matlab程序（MOQPSO）,用户可以根据需求自己更换目标函数(this is an multi-collapse Orthogonal cross quantum-behaved particle swarm optimization program of matlab，the user can revise the Object function for your need.)

this is a matlab program

压缩感知中求解最优L1范数问题的BP算法内含指导文章(Compressed sensing in L1 norm to solve the problem of optimal BP algorithm article contains guidance)

public guideness for swarm Ops in Matlab

特征降维方法，其中包含有典型的特征组合方式——PCA和特征选择中的SFFS，SBS，SFS。共四类常用的特征降维方式。(different features dimensionality reduction methods.)

matlab中的离散卷积函数。。。。。。(discrete convolution in matlab)

MATLAB应用大全一书的配书光盘第二章源代码,该文件夹收录了本书涉及的源文件。收录了一些优秀应用实例信息，便于读者学习了解。(MATLAB application of CD attached with books of chapter iii source code, this folder contains the book files. Includes some excellent examples of application information, convenient for readers to learn. )

The basic steps of the connected-component text extraction algorithm are given below, and diagrammed in Figure 10. The details are discussed in the following sections. 1. Convert the input image to YUV color space. The luminance(Y) value is used for further processing. The output is a gray image. 2. Convert the gray image to an edge image. 3. Compute the horizontal and vertical projection profiles of candidate text regions using a histogram with an appropriate threshold value. 4. Use geometric properties of text such as width to height ratio of characters to eliminate possible non-text regions. 5. Binarize the edge image enhancing only the text regions against a plain black background. 6. Create the Gap Image (as explained in the next section) using the gap-filling process and use this as a reference to further eliminate non-text regions the output.