arxIdentify

用esprit算法估计复正弦加白噪声的信号频率，f给出正弦信号的频率估计值(Esprit algorithm with an estimated increase in complex white noise sinusoidal signal frequency, f the frequency of sinusoidal signal given the estimated value of)

介绍国内外机械故障诊断技术的发展情况，并列举了应用实例。(Describes the development of domestic and foreign machinery fault diagnosis technology, and examples of its applications.)

一款基于matlab环境开发的系统辨识工具箱。主要涉及频域辨识算法，除了常规的辨识方法之外，还包括状态空间辨识。内有pdf的使用说明。(A matlab toolbox for system identification in frequency domain.)

this coding use for students who use matlab steganography. the code will be highly used in recent times.

冒险咖啡屋秘密花园V35最终版源码 Visual Basica代码，要研究MXD的朋友可以下载看下(adventure coffee secret garden V35 final version of Visual Basica source code to study MXD friends can download facie)

model baraye Cp power extraction

介绍一些小波函数的基本功能和常用函数，并举例(Introduce some basic functions and wavelet functions commonly used functions and an example)

通过matlab仿真工具仿真分析了APSK调制方式在典型的加性高斯白噪声下的传输性能(Through simulation matlab simulation tool analyzes APSK modulation in a typical additive white Gaussian noise transmission performance)

这是一些关于人脸识别的MATLAB程序，主要对人脸清晰度的处理，可以使图形信息更加的清晰，希望对大家有好的方面(This is some of the MATLAB program on the face recognition, mainly on the treatment of facial definition, can make information more clear graphics, I hope all of you there are good aspects of)

说明：  SGA（Simple Genetic Algorithm）是一种强大的智能多变量优化算法，它模仿种群繁殖规律来进行优化。本SGA可以优化变量，求最小值,最大值（当把函数倒数也就求最小值） 并且支持浮点编码，grey编码，二进制编码；轮赌法选择，锦标赛选择；单点交叉，均布交叉，浮点交叉；单点变异，浮点变异；调用时Genetic（目标函数名） 使用SGA时，首先需要一个目标函数（像AimFunc.m），该函数返回适应度输入变量为待优化变量x输出为一个适应度。然后修改Genetic.m中可以修改的地方(SGA (Simple Genetic Algorithm) is a powerful smart multi-variable optimization algorithm, which mimics the reproduction of law to be optimized. The SGA can be optimized variables, minimum, maximum, (when the function will last for the minimum) and supports the floating-point encoding, grey code, binary code round of betting method selection, tournament selection single-point crossover, uniform crossover , floating-point crossover single point mutation, floating-point mutation called Genetic (objective function name) the use of SGA, first of all need an objective function (like AimFunc.m), the fitness function returns the input variables to be optimized for the output variable x a fitness. Can be modified and then modify the place Genetic.m)