AGuidetoMATLABforBeginnersandExperiencedUsers

Kalman滤波的matlab程序，用于求解舰船的姿态航向角(Kalman filter matlab program for solving attitude and heading angle of the ship)

基于matlab的语音识别代码（使用HMM算法的）(Matlab speech recognition code (using the HMM algorithm))

Using SeDuMi 1.02. A Matlab toolbox for optimization over symmetric cones

用于做统计分析的matlab 程序包,各种基本统计分析的函数都有，很好用。(For matlab to do statistical analysis package, a variety of basic statistical analysis functions are well used.)

its usage is in computer vision

用matlab仿真实现ldpc编解码，BPSK调制, 测定误码率与信噪比的关系(Using matlab simulation to realize LDPC Encoding and decoding, BPSK modulation, and to determine the relationship between bit error rate and signal-to-noise ratio)

this file simulate a mimo system

OFDMA仿真代码,可以直接运行，包含很多M文件，可以分块使用，非常有用。(OFDMA simulation code can run, including a lot of M file, you can block use, very useful.)

说明：  分数阶傅里叶变换，一维的分数阶傅里叶变换matlab程序(Fractional Fourier transform)

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.