CV

《matlab7从入门到精通》是一本很经典的入门级教科书，文件中包含了书中所有源码(" Matlab7 From Novice to Professional" is a classic entry-level textbook, the book file contains all the source code)

单级倒立摆二级倒立摆simulink model and mutiple control aglorithms Full order observer Full order observer with Kalman filter Poleß Placement method LQR optimization(Single-stage inverted pendulum inverted pendulum simulink model and mutiple control aglorithms Full order observer Full order observer with Kalman filter Poleß Placement method LQR optimization)

matlab中，利用偏最小二乘法优选最佳波长，构建模型，拟合方程(PLSR, a dimensionality reduction method, is emerging as the most robust and reliable chemometric method for constructing models and aims at determining predictor combinations with maximum covariance with the response variable when the measured variables are many and highly collinear)

数据融合 ，航迹估计，单目标的航迹估计，自己做了，预测效果还不错(data fusion Track estimation)

这个是空间谱估计中阵元互耦校正算法，自己写的。(This is the spatial spectrum estimation Mutual Coupling correction algorithm, wrote it myself.)

MOPSO算法有详细说明，能够良好运行，出pareto图(MOPSO algorithm is described in detail, able to run well, generate the Pareto Diagram)

蒙特卡洛(Monte Carlo)方法，是一种基于计算机“随机数”的计算方法。(Monte Carlo (Monte Carlo) method, is a computer-based " random" is calculated.)

说明：  MATLAB非线性滤波工具箱 在“中国国防科技论坛 ”找到的 (Nonlinear Filtering in MATLAB toolbox China National Defense Science and Technology Forum found)

一维云发生器，matlab编写，比较好用(the yun generator which is good)

function [L,C] = kmeans(X,k) KMEANS Cluster multivariate data using the k-means++ algorithm. [L,C] = kmeans(X,k) produces a 1-by-size(X,2) vector L with one class label per column in X and a size(X,1)-by-k matrix C containing the centers corresponding to each class. Version: 07/08/11 Authors: Laurent Sorber (Laurent.Sorber@cs.kuleuven.be) References: [1] J. B. MacQueen, "Some Methods for Classification and Analysis of MultiVariate Observations", in Proc. of the fifth Berkeley Symposium on Mathematical Statistics and Probability, L. M. L. Cam and J. Neyman, eds., vol. 1, UC Press, 1967, pp. 281-297. [2] D. Arthur and S. Vassilvitskii, "k-means++: The Advantages of Careful Seeding", Technical Report 2006-13, Stanford InfoLab, 2006.