duozitizifushibie

说明：  多变量寻优的源码，包括基本算法如下：DFP法（又称变尺度法），BFS法、一阶梯度法，共扼梯度法。(multivariate optimization of the source code, including basic algorithm is as follows : DFP Act (also known as the variable scale), BFS, a ladder degrees, a total of the accused gradient method.)

模糊聚类分析动态聚类分析程序，很简单，实用。附带有聚类图程序(Dynamic fuzzy clustering analysis Cluster analysis procedure is very simple and practical. Figure comes with a clustering procedure)

比较了三种学习方法 1 gradient descent 2 steepest descent with line search 3 conjugate gradient method. 三种方法都在一个.m文件中被实现。(compare three learning methods: 1 gradient descent 2 steepest descent with line search 3 conjugate gradient method.)

Matlab_show calculation of average and higuchi

信号系统上机实验代码与指导书，采样、连续卷积、连续运算、连续系统(Machine experimental code and instructions on signal systems, sampling, continuous convolution, continuous operation, continuous system)

在matlab环境中自动识别连通区域的大小,时间序列数据分析中的梅林变换工具，用MATLAB实现的压缩传感。( Automatic identification in the matlab environment the size of the connected area, Time series data analysis Mellin transform tool, Using MATLAB compressed sensing.)

将图形加以高斯噪声或者椒盐噪声。为图像处理的一种可靠的加噪方法。BLUR Test problem: digital image deblurring(Gaussian noise or the graphics to be salt and pepper noise. As a reliable image processing method with noise. BLUR Test problem: digital image deblurring)

MIMO雷达发射方向图设计源码，大家可以参考(MIMOradar transmit beampattern)

k程序差分进化工具箱 - DeMatMATLAB包括拥有数百个内部函数的主包和三十几种工具包。工具包又可以分为功能性工具包和学科工具包。功能工具包用来扩充MATLAB的符号计算，可视化建模仿真，文字处理及实时控制等功能。学科工具包是专业性比较强的工具包，控制工具包，信号处理工具包，通信工具包等都属于此类。(k programs differential evolution toolbox- DeMatMATLAB including internal functions with hundreds of primary packages and several 30 kits. Kits can be divided into functional disciplines toolkit and toolkit. Function tool kit used to expand the MATLAB symbolic computation, visualization, modeling and simulation, word processing, and real-time control functions. Discipline tool kit is relatively strong professional toolkit, Control Toolkit, signal processing toolkit, communications toolkit belong to this category.)

该程序实现了马尔科夫蒙特卡洛模拟方法，是贝叶斯估计不可缺少的程序(this algorithm realise Markov-monte carol algorithm and is indispensible for Bayesian estimation.)