A1_14

系统系统辨识文件夹内是产生高斯白噪声，m序列和最小二乘法的一次完成算法，递推算法，限定记忆法的程序。系统仿真文件夹内是对系统线性和非线性的建模和仿真程序。(System folder on system identification is to generate Gaussian white noise, m sequence and a complete least-squares method algorithm, recursive algorithm, limited memory method procedures. System Simulation System folder is a linear and nonlinear modeling and simulation program.)

说明：  里面有不少MATLAB学习课件,对新手很有帮助。(there are many study matiarial)

计数型抽样检验分析程序 按超几何分布计算(Counting of sampling inspection procedures by calculating the hypergeometric distribution)

Comparative Performance Analysis of Wireless Communication Protocols for Intelligent Sensors and Their Applications

有记忆预失真处理程序，可以实现对PA转换下饱和失真的处理(Predistortion with memory processes can be achieved under the PA saturation distortion conversion process)

基于matlab用于求解商人过河问题，运用随机模拟的思想得到问题的多个解(Matlab-based businessman river used to solve the problem, the idea of ​ ​ using stochastic simulation of multiple solutions to get the problem)

说明：  通常，非线性整数规划是一个具有指数复杂度的NP问题，如果约束较为复杂，Matlab优化工具箱和一些优化软件比如lingo等，常常无法应用，即使能应用也不能给出一个较为令人满意的解。这时就需要针对问题设计专门的优化算法。下面举一个遗传算法应用于非线性整数规划的编程实例，供大家参考！(Generally, nonlinear integer programming is a NP problem with exponential complexity. If the constraints are more complex, MATLAB optimization toolbox and some optimization software such as lingo are often unable to be applied, even if they can be applied, they cannot give a satisfactory solution. At this time, we need to design a special optimization algorithm for the problem. Here is an example of genetic algorithm applied to nonlinear integer programming, for your reference!)

The Levenberg–Marquardt Method writed by Lourakis

有源自适应噪声的最常用算法之一，该算法是另一个基于最小二乘准则的精确方法，它具有快速收敛和稳定的滤波器特性。(Active adaptive noise, one of the most commonly used algorithm, the algorithm is another accurate method of least squares criterion, it has fast convergence and stability of the filter characteristics.)

变分模态分解,用于分解各种信号，可用来故障诊断，特征提取。(Variational mode decomposition, used to decompose various signals, can be used for fault diagnosis and feature extraction.)