leveldiagramBeta2008

里面有详细的反步法仿真的例子，共有9个实例。非常适合初学者使用。(There are detailed examples of backstepping simulation, a total of 9 examples. It is very suitable for beginners.)

计算常用指标Gmean,F-score,sensitivity,specificity,precision,roc和auc曲线，输入test_label,predict_label两个列向量，即可获得以上指标(calculate some indexes)

短时傅里叶变换实现线性调频信号的时频分析(Time-frequency analysis of LFM signal by short time Fourier transform)

自己编写的COST207 MATLAB信道模型 包括RA TU BU RA 等不同环境下信道参数等(I have written COST207 MATLAB channel model including the RA TU BU RA channel parameters under different circumstances)

search of FAD for motion estimnation

说明：  最优化理论与方法 课本算法 matlab实现 单纯形法(对偶) 具体使用方法见程序说明~(Optimization theory and method to achieve textbook algorithm matlab simplex method (dual) specific description of the procedures to use, see ~)

雷达信号检测和信息提取:根据雷达接收到的信号检查是否含有目标反射回波，并从反射回波中测出有关目标状态的数据。信号是信息的载体，信息是信号的内容。雷达工程界习惯于把雷达信号检测和信息提取的具体实施称为雷达信号处理，并把这种处理与测出的数据的处理合称为雷达信息处理。技术科学界最初把采用数理统计工具解决这一类信息处理的理论问题称为检测理论，后又称为检测与估计(Radar signal detection and information extraction, according to the received radar signal check whether contain the target echo, and measure the echo data on target state.Signal is the carrier of information, the content of the information is a signal.Radar engineering is used to the specific implementation of the radar signal detection and information extraction called radar signal processing, and the processing and the processing of measured data as radar information processing.Technology of the scientific community initially put the use of mathematical statistics tools to solve this problem is known as a kind of information processing theory testing theory, also known as the detection and estimation)

MATLAB 6.0 数学手册 对于初学者来说 很好的一本书，希望你们能用得到！(MATLAB 6.0 math handbook for beginners a good book, I hope you can get! )

多变量非线性优化模型求解，对约束条件建立m文件(Multi-variable nonlinear optimization model for solving the establishment of restrictive conditions on m file)

【数学仿真软件】Computational Statistics Handbook with MATLAB的源代码([T]his book is perfectly appropriate as a textbook for an introductory course on computational statistics. It covers many useful topics, which in combination with the well-documented code, make the underlying concepts easy to grasp by the students)