Matlab_ex

压缩包里面有四个函数，实现了常用的几种模糊聚类方法，附有较详细的注释(There are four functions in the file. these functions fulfills common method of fuzzy cluster. Commments are quite good)

基于HMM的说话人识别系统，包括提取MFCC特征，特征对比等。(A speaker recognition system based on HMM,included the extraction of MFCC features and features comparison)

说明：  用ＭＡＴＬＡＢ里边带的ＬＰＣ程序进行参数提取.(MATLAB inside with the LPC parameter extraction procedures.)

lingo小程序，解决线性规划问题，如最优下料问题等。希望对从事这方面的朋友有帮助。(lingo small program to solve linear programming problems, hope in this field to help a friend.)

单级倒立摆控制 此程序用在过程控制中，仿真软件为Matlab(Single Link Inverted Pendulum Control)

使用costas环实现载波同步，绘制出了载波频率跟踪曲线(Achieve carrier synchronization using the costas loop, draw the curve of the carrier frequency tracking)

已知地图边界点通过插值求面积，matlab计算面积函数实现。(Known map boundary points by interpolation for the area, matlab calculate the area function implementation.)

详细介绍了3G方案中WCDMA的无线资源管理并给出了仿真方法，在Matlab软件下进行了模拟(Details of the 3G program WCDMA radio resource management and simulation methods in Matlab software, a simulation carried out under)

本文档介绍了如何在c++环境下调用MATLAB(This document describes how to call c++ environment MATLAB)

Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction, yielding gains in algorithm performance and complexity and in data storage. This paper introduces a new minimum mean square error-based approach to infer the signal subspace in hyperspectral imagery. The method, which is termed hyperspectral signal identification by minimum error, is eigen decomposition based, unsupervised, and fully automatic (i.e., it does not depend on any tuning parameters). It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. State-of-the-art performance of the proposed method is illustrated by using simulated and real hyperspectral images.