3small-s

利用MATLAB编写了GM（1，1）预测模型的程序，方便人们直接使用该程序进行预测。(MATLAB prepared using GM (1,1) prediction model of the procedures for people to direct the use of the prediction process.)

基于MATLAB的QPSK过程编程,并且对其过程的信号流程进行分析,用星座图分析其误码率(The QPSK based on MATLAB programming process, and its process of signal flow analysis, using the constellation diagram to analyze the bit error rate)

基于傅里叶分析的信号延时测量，采用FFT方法，对同一频率的两个信号进行频谱分析，测得相位差(Delay measurements based on Fourier analysis of signals using the FFT method for spectral analysis of the two signals of the same frequency, the measured phase difference)

用于基于图像纹理特征提取的图像检索，其中包括matlab中自带的graycomatrix和graycoprops两个m文件，和四个用于提取图像纹理特征及图像检索的m文件(For image retrieval, including matlab comes graycomatrix, and graycoprops two m files, and four m-files used to extract image texture features and image retrieval based on image texture features extracted)

PSAT包含了：PF-潮流计算；CPF-连续潮流；OPF-最优潮流；SSSA-小扰动分析；TDS-时域仿真；GUI-用户人机界面；GNE-自定义模型等功能。该工具包已经可以计算上千节点规模的系统。而且该软件包源代码完全公开，因此用户可以根据自己的研究兴趣编写修改相应源代码实现研究目的。(PSAT includes: PF-flow calculation CPF-continuous fashion OPF-OPF SSSA-small perturbation analysis TDS-time domain simulation GUI-user machine interface GNE-custom models and other functions. The kit can have thousands of computing nodes scale systems. And the package source code is completely open, so that the user can modify the source code to write research purposes according to their research interests.)

MATLAB中的所有练习源程序,软件包形式,对学习MATLAB很有帮助(MATLAB source code for all exercises, the package forms of learning MATLAB helpful)

this code implemented for ICA algorithm and can be use for face recognition

光伏MPPT最大功率跟踪仿真模型，很有参考价值的算法(Photovoltaic maximum power tracking of MPPT simulation model, the algorithm of great reference value)

Tactial+and+Strategic+Missile+Guidance book program source code (For Mac in Matlab)

《MATLAB神经网络30个案例分析》中的第一个例子，案例1 BP神经网络的数据分类-语音特征信号分类。希望对大家有用！ (" MATLAB neural network 30 case studies" in the first example, case 1 BP neural network data classification- speech feature signal classification. I hope useful!)