shujuchuli

matlab图像处理领域类的一种常用算法。对初学者有很大的帮助(matlab image processing class, a common algorithm. Very helpful for beginners)

浮动顺序搜索算法搜索特征空间生成候选子集(Sequential floating search algorithm to search a subset of the feature space generated candidate)

很多程序的集合，在日常生活中必须的算法大全(A collection of many programs, in their daily lives must be an algorithm Daquan)

说明：  matlab中similink入门指南。希望能够大家有些帮助，尤其对于刚刚入门的朋友。(matlab in similink Getting Started Guide. Some hope to be able to help everyone, especially for entry-just friends.)

基于Anti-我indupdePID控制 包含M语言和Simulink仿真(I indupdePID Anti-based control language and Simulink simulation contains M)

图像增强：空域增强；灰度直方图；平滑滤波器和锐化滤波器的使用；图像中值滤波增强的使用；低通滤波器和高通滤波器的使用 (Image Enhancement: Enhanced airspace gray histogram use of the smoothing filter and sharpening filter the use of the enhanced image median filtering the use of low-pass filter and high-pass filter)

相邻系数引入到小波变换，用局域均值分解特征提取(Adjacent coefficient is introduced into the wavelet transform, using the local mean decomposition feature extraction)

说明：  处理旅行商问题的离散PSO算法的例程，动态生成路径串，算法本身保证了路径串的合法性(Traveling salesman problem to deal with discrete PSO algorithm routines, dynamically generated path string, the algorithm itself, guarantee the legitimacy of the path string)

利用matlab编程实现的大数据处理工具，通过分析数据规律，得到其最佳分布参数(Programming using matlab big data processing tools, by analyzing the data rule to obtain the optimal distribution parameters)

波达方向（DOA） 估计的基本问题就是确定同时处在空间某一区 域多个感兴趣的信号的空间位置(即多个信号到达阵列参考阵元的方 向角)。最早的也是最经典的超分辨率(DOA)估计算法是著名的多信号 分类（Multiple Signal Classification） 法,简称 MUSIC 算法,它是 一类经典的基于特征结构分析的空间谱估计方法。该算法利用了信号 子空间和噪声子空间的正交性,构造空间谱函数,通过谱峰搜索,检测 信号的 DOA。(The basic problem of DOA estimation is to determine the simultaneous location in a certain region of space. Spatial position of multiple interested signals in the domain (i.e. the direction of multiple signals reaching the array reference elements) Directional angle). The earliest and most classical super-resolution (DOA) estimation algorithm is the well-known multi-signal.Multiple Signal Classification, referred to as MUSIC algorithm, is A classical spatial spectrum estimation method based on eigenstructure analysis. The algorithm utilizes signals. The orthogonality of subspace and noise subspace, the construction of spatial spectral function, through peak search, detection DOA of signal.)