matlab-optimaiztion

一个梯度优化算法的实例(演示)。。。。线性判别分析的伪逆算法程序（matlab6.5）(A gradient optimization algorithm examples (demo). . . . Linear Discriminant Analysis of the pseudo-inverse algorithm procedure (matlab6.5))

说明：  几种传统的图像插值放大方法：最近邻插值法，双线性插值法，双三次插值法(Several traditional interpolation to enlarge the image : nearest neighbor interpolation, bilinear interpolation, bicubic interpolation.)

MATLAB的基本操作实现：P0201：MATLAB赋值，MATLAB中的for循环，MATLAB中的for循环和if条件，MATLAB图像处理的基本操作，MATLAB高级图像处理操作，根据RGB图像创建一幅灰度图像，二值图像的取反操作，用imshow函数显示图像，在同一个窗口内显示两幅图像(MATLAB' s basic operations to achieve: P0201: MATLAB assignment, MATLAB in the for loop, MATLAB in the for loop and if conditions, MATLAB image processing basics, MATLAB high-level image processing operations, according to RGB image to create a grayscale image, two negated the value of the image operation to display images with the imshow function, in the same window display two images)

求卷积及两个序列的互相关函数，或一个序列的自相关函数；(for convolution and two sequences of cross-correlation function, or a series of auto-correlation function;)

入门好书《MATLAB神经网络30个案例分析》，连同源程序，许多应用范例(good book for matlab ANN)

编程仿真连续小推力实现GTO到GEO的三阶段转移过程，其中推力器的推力大小为0.8N，轨道机动的起始点为GTO的远地点。GTO轨道的升交点赤经为0度，近地点角距为90度。 GTO轨道： ph:185km，ah：35786km，i：28.5°，GEO轨道：h：35786km，i：0°。 卫星质量为6600kg，从GTO到GEO，采用5000s的推力器。取地球半径为6378km，g取值为9.8m/s^2(The three stage transfer process from GTO to GEO is realized by simulation and continuous small thrust. The thrust of the thruster is 0.8N, and the starting point of orbital maneuver is the apogee of GTO. GTO orbit RAAN is 0 degrees, 90 degrees for the argument of perigee. GTO orbit: ph:185km, ah:35786km, i:28.5, GEO orbit: h:35786km, i:0. The mass of the satellite is 6600kg, from GTO to GEO, using the 5000S thruster. The radius of the earth is 6378km, and the value of G is 9.8m/s^2)

the newer version from HMMbox 3.2 Matlab toolbox for Variational estimation Hidden Markov Models. (Adapted from Hidden Markov Toolbox Version 3.3 01-Apr-99 and Coupled Hidden Markov Toolbox Version 1.1 01-Feb-01 Copyright (c) by Iead Rezek, Oxford University) The software uses some NETLAB routines (see http://neural-server.aston.ac.uk/netlab/index.html so you ll need to have NETLAB on your search path See the file VERSION for what s new in this version. The observation models has so far been implemented are Gaussian, Poisson and Dirichlet

2D Wave equation Model forwarding by the method of pesudo-spectrum.

球型机器人路径跟踪算法。 路径跟踪带带干扰 非线性PID算法(1. Circle following Parameter selection：Euler Fixed-step size:0.001 2. Run: first "robot_sim" and then "robot_plot" )

验模态分解（Empirical Mode Decomposition,简称EMD）是一种自适应信号分解方法,主要应用于非线性非平稳的信号。整体平均经验模态分解（Ensemble Empirical Mode Decomposition,简称EEMD）解决了EMD中出现的模态混合问题。(Ensemble Empirical Mode Decomposition)