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基于汉宁窗的fir带通滤波器 用matlab仿真(Hanning window on the fir bandpass filter simulation using matlab)

系统讲述了matlab在数学建模中的应用，有助于良好的掌握matlab的工具箱使用和进一步了解matlab的强大功能。(Matlab system described in the application of mathematical modeling to help a good grasp of the matlab toolbox to learn more about the use and power of matlab.)

空间平滑MUSIC算法的MATLAB程序，适用于DOA估计，程序简单易懂，非常适合于刚入门的同学(Space Music Algorithm)

维特比算法8*8的实现。适用于数字通信原理的卷积码章节的学习。(viterbi algrithem)

pid自适应控制器学习和程序大家学习，很好用的(点对点)

希尔伯特-黄变换的代码，适用于分析非平稳信号(Hilbert-Huang Transform code applicable to the analysis of non-stationary signals)

jade algorithm for extration of features

本资源主要对矩阵分解中的LU分解、LDL’分解、乔列斯基分解，以及无约束最优化领域中的最速下降法、牛顿法、拟牛顿法的原理、步骤和算法进行了简要介绍，并对各种方法进行了Matlab编程实验，得到了较好的结果。 本资源包含了《矩阵分解及无约束最优化方法的原理和应用简介》文档以及其中用到的全部Matlab程序，非常适合初学者学习与研究。(The resources are mainly in the matrix decomposition LU decomposition, LDL decomposition, Cholesky decomposition, and unconstrained optimization field steepest descent method, Newton s method, the principle of quasi-Newton methods, procedures and algorithms are briefly introduced, and various methods of Matlab programming experiment, get a better result. This resource contains a matrix decomposition and unconstrained optimization methods Introduction to the principles and applications which uses all the documents and Matlab program, ideal for beginners learning and research.)

逐步判别分析的主函数 用于分类 [sel,c,c0,re,P]=StepclaassV2(data,[50 50 50],data,10) 输入变量 x为训练集.每行为一个样本，每列为一个变量. Class_x,为训练集的分类情况，一行，为各类样本数量,例如[5 6 9] Test为待分类样本. 输出变量：sel为选择的变量序号，c,c0为拟合出的判别函数.re为对Test的判别结果,P为其后验概率. author 王新 2012.4.8 例子Sample: load fisheriris x=meas Class_x=[50,50,50] Test=meas(1:5,:) Fa1=4 [sel,c,c0,re,P]=StepclaassV2(x,Class_x,Test,Fa1)( Stepwise discriminant analysis for the classification of the main function [sel, c, c0, re, P] = StepclaassV2 (data, [50 50 50], data, 10) input variables x as the training set, each conduct a sample of each as a variable. Class_x, the classification for the training set, a row, the number of samples for all types, for example, [5 6 9] Test sample to be classified. output variable: sel for the selected variables serial number, c, c0 is fitted discriminant function. re discrimination results for the Test, P its posterior probability. author Wang 2012.4.8 examples Sample: load fisheriris x = meas Class_x = [50,50,50] Test = meas (1:5, :) Fa1 = 4 [sel, c, c0, re, P] = StepclaassV2 (x, Class_x, Test, Fa1))

matlab讲义，附带部分源代码，是一份不错的学习matlab资料，哪个学校的忘记了。(matlab handouts, incidental part of the source code, is a good study matlab data, which schools have forgotten.)