ziyoushouxieti

本程序使用Shuey方程完成三层界面的正演模拟 子波使用雷克子波(This program uses the Shuey equation, a three-forward simulation interface using Leike Zi wave wavelet)

matlab函数逼近程序，里面包括了常用的matlab函数逼近的程序，包括手写的和matlab自还的函数。(matlab function approximation process, which includes the commonly used matlab function approximation procedures, including hand-written and self is also a function of matlab.)

运用UKF算法对GPS和惯导信息进行了组合导航和信息融合，采用的是松组合方式(integrated navigation and information fusion of SINS/GPS based on UKF)

典型的量子遗传算法，求解最值问题,绝对没有密码(The typical quantum genetic algorithm is the most value problems)

遗传算法解非线性问题，0－1整数规划，附图表，实例(Genetic Algorithm for Nonlinear 0-1 integer programming problems, drawing tables, examples)

使用遗传算法对BP网络权值阈值进行优化，再用BP算法训练网络(BP network using genetic algorithm to optimize the weight threshold, and then BP algorithm for training the network)

先进PID控制MATLAB仿真(第3版), 作者: 刘金琨,4、5部分源码(Advanced PID control MATLAB simulation (3rd edition), Author: Jinkun, 4,5 some source)

说明：  我的智能控制作业，球—横木控制系统matlab仿真程序。程序及仿真模型，结果都有。(intelligent control operations, the ball-ledger control system Matlab simulation program. Procedures and simulation models, results have.)

广义预测控制里，对象参数未知条件下的GPC自适应算法(Generalized predictive control, the object under unknown parameters of GPC adaptive algorithm)

不错的GM_EM代码。用于聚类分析等方面。( GM_EM- fit a Gaussian mixture model to N points located in n-dimensional space. Note: This function requires the Statistical Toolbox and, if you wish to plot (for k = 2), the function error_ellipse Elementary usage: GM_EM(X,k)- fit a GMM to X, where X is N x n and k is the number of clusters. Algorithm follows steps outlined in Bishop (2009) Pattern Recognition and Machine Learning , Chapter 9. Additional inputs: bn_noise- allow for uniform background noise term ( T or F , default T ). If T , relevant classification uses the (k+1)th cluster reps- number of repetitions with different initial conditions (default = 10). Note: only the best fit (in a likelihood sense) is returned. max_iters- maximum iteration number for EM algorithm (default = 100) tol- tolerance value (default = 0.01) Outputs idx- classification/labelling of data in X mu- GM centres)