chap10_2

在matlab环境下，实现kalman滤波器跟踪目标。(in Matlab environment, the Kalman filter to track the realization of goals.)

此程序为MATLAB计算非线性方程组的程序(This procedure for calculating the nonlinear equations MATLAB procedure)

rinex file observasion

Root Locus Design tool for function

用matlab编写的一段感知器神经网络代码，挺好用的(Prepared using matlab a perceptron neural network code, very good use)

matlab code for finite element method

在matlab上运用有限时域差分法模拟二维光子晶体(the simulation of tm mode in two-dimensional photonic crystals using FDTD)

matlab的绘图教程，详细介绍matlab绘图指令，语法(matlab drawing tutorials, detailed graphics matlab command syntax)

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.

将图像分为16*16的分块进行计算,稀疏矩阵采用DCT矩阵，观测矩阵采用高斯随机矩阵，重构采用OMP算法,对256*256大小的8bit灰度lena图像进行仿真( )