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图像认证技术，源码最新下载自美国名校The University of Texas at Austin的Brian L. Evans教授的实验室网站 (Matlab programs for image authentication downloaded from Professor Brian L. Evans in University of Texas at Austin in USA)

LTE-Advance信道预编码矩阵构造的matalb仿真程序，具有很好的使用价值。(LTE-Advance-channel pre-coding matrix simulation program constructed matalb has good value in use.)

Particle filter source code in matlab

Underdetermined Blind Source Separation

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Fingerprint source code

很多代数方程组的解法，需要用matlab做算法的童鞋可以考虑下载(Solution of many algebraic equations, need to do the algorithm matlab download children s shoes can be considered)

分别用非参数化谱估计中的直接法，间接法和加窗法对离散随机过程的已零均值化的N个数据样本估计了离散信号的谱密度。(Were non-parametric spectral estimation of the direct method, indirect method and windowing method, discrete stochastic process has zero mean the data of the N-sample estimates of the spectral density of discrete signals.)

MUSIC算法[1] 是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成。MUSIC算法就是利用这两个互补空间之间的正交特性来估计空间信号的方位。噪声子空间的所有向量被用来构造谱，所有空间方位谱中的峰值位置对应信号的来波方位。MUSIC算法大大提高了测向分辨率，同时适应于任意形状的天线阵列，但是原型MUSIC算法要求来波信号是不相干的。(algorithm MUSIC is a method based on matrix feature space decomposition. From a geometric point of view, the signal processing of the observation space can be decomposed into signal subspace and noise subspace, it is clear that these two spaces are orthogonal. Signal subspace by the array received data covariance matrix and signal corresponding to the feature vector and noise subspace is by the covariance matrix of all minimum feature values (noise variance) corresponding to the feature vectors are composed. MUSIC algorithm is to use the orthogonal characteristics of these two complementary space to estimate the azimuth of spatial signals. All vectors of the noise subspace are used to construct spectral, and the peak position in all spatial azimuth spectra correspond to the direction of arrival of the signal. MUSIC algorithm greatly improves the direction finding resolution, and at the same time it is suitable for the antenna array of any shape, but the prototype MUSIC algorithm requir)

说明：  数据统计描述 第一节 数据分析中常用的统计量及其分布 第二节 频数变量数据特征描述 第三节 综述变量数据特征的描述 第四节 数据分析过程的记录与重现(Data described in section I of data analysis commonly used in statistics and their distribution in section II, the frequency characteristics of variable data variables described in Section III Summary data on the characteristics of the process of data analysis described in section IV of the record and reproduce)