GLRect

2opt metaheuristic algorithm greedy

在Matlab中，用PCA程序提取两个统计量：T2和Q从而应用在机械故障的预测中，我个人觉得还可以，希望大家指正。(In Matlab, with the PCA program to extract the two statistics: T2 and Q and thus used in the prediction of mechanical failure, I personally felt that I can and hope that we corrected.)

先进PID控制及其MATLAB仿真程序第三部分(Advanced PID Control and MATLAB Simulation Program Part III)

在本程序中，轻松实现了阵列信号角度的估计。(In this program easily estimate of the angle of the array signal)

文件包含现代信号处理的常用算法的matlab源代码(Document contains commonly used in modern signal processing algorithm matlab source code)

加有高斯白噪声的两个正弦信号的的观测数据，分别用最小二乘法和总体最小二乘法估计其功率谱，并对两种方法的谱分析进行了比较(Plus a Gaussian white noise of the two sinusoidal signals of observational data, were used least squares and total least squares method to estimate the power spectrum, and spectral analysis of the two methods were compared)

实验一：三次样条插值（P56，例6） 一、实验目的： 1) 掌握三次样条插值的运用 2) 了解拉格朗日插值在高次上的误差 二、实验环境：Matlab6.5 三、实验内容： 1) 给定函数f(x)=1/(1+x2)，-5<=x<=5，节点xk=-5+k，(k=0,1,2…10)，用三次样条插值求S10(x)，S10’(-5)=f’(-5)，S10’(5)=f’(5)。 2）作原函数f(x)，拉格朗日插值函数Ln(x)，三次样条差值函数Sn(x)。画出三个函数的图像，比较它们的区别。 (Experiment I: cubic spline interpolation (P56, cases of 6) First, the experiment was: 1) cubic spline interpolation to master the use of 2) understanding of Lagrange interpolation in high-error second, experimental environment: Matlab6 .5 c, experimental elements: 1) a given function f (x) = 1/(1+ x2),-5 <= x <= 5, node xk =- 5+ k, (k = 0,1,2 ... 10), using cubic spline interpolation for S10 (x), S10 (-5) = f (-5), S10 (5) = f (5). 2) for the original function f (x), the Lagrange interpolation function Ln (x), cubic spline difference function Sn (x). Draw the three functions of images, compare the difference between them.)

基于神经网路的遥感图像分类，使用神经网络对几幅不同频段的遥感图像分类，主要是区分图像中不同的地形区域。(Neural network-based remote sensing image classification, the use of neural networks on a number of different band remote sensing image classification, mainly to distinguish between images of different regions of the terrain.)

利用单应点进行透视反变换，matlab实现(Perspective inverse transform, matlab achieve)

The goal of this program is to demonstrate the construction of a huffman encoding tree. The tree is represented as a binary tree using MATLAB s built in treeplot commands. Contruction of the tree as well as the huffman code book will be described in later sections