FastICA_25

支持向量机工具箱 可以借助此工具箱完成很多信号的处理(failed to translate)

lt码的编译码，译码方式为bp译码，源码的比特数可以自己设定(lt code encoding and decoding, decoding method for the bp coding, source bits can be set)

cognitive radio performance matlab code for spectrum sensingg

迭代最近点算法的一个简单实现，并使用了两个二维点集进行测试(an implementation and validation for the data association of two 2d point sets based on iterative closest points)

针对非圆信号DOA估计问题,提出了一种基于实值特征值分解 (Eigenvalue decomposition,EVD)的求根MUSIC算法.首先利用非圆信号为实值信号的特点,将阵列上的接收数据及其共轭用欧拉公式转换为实值正弦与 余弦数据,然后将正弦与余弦数据进行串联,从而扩展了数据维数.由于采用实值矩阵的EVD,因此在EVD阶段的运算量简化为复值EVD的1/4.根据 EVD后获得的信号与噪声子空间的特点,对噪声子空间和导向矩阵进行重构以便于可以使用求根MUSIC算法获取对DOA的估计.仿真实验验证了本文算法的 有效性(For the estimation of noncircular signals of DOA, proposes a decomposition value based on real valued features (Eigenvalue decomposition, EVD) the root MUSIC algorithm. Firstly, characteristics of non circular signals for real valued signals, the array data and its conjugate with the Euler formula into real value of sine and cosine and sine and cosine data. The data series, thus expanding the dimension of the data. Because of the use of real valued matrix computation in EVD, so the EVD stage was simplified as a complex valued EVD 1/4. according to the characteristics of signal and noise subspace is obtained after EVD, the noise subspace and orientation matrix reconstruction in order to facilitate the use of DOA can obtain the estimated root MUSIC the algorithm. The simulation results verify the effectiveness of the proposed algorithm)

卷积码的最大后验概率译码算法的一个验证matlab算法，必有注释。(Convolutional codes of maximum a posteriori probability decoding algorithm matlab an authentication algorithm, there is the Notes.)

how to construct the parity check matrix for LDPC codes

5th exercise of computer graphics course

黄金分割法，附带说明，程序可直接运行,,有实例说明，是数值最优化方面的(Golden section method, with instructions, the program can be run directly)

EMD或者LMD的能量密度与其平均周期的乘积K值，当K值发生较大变化的时候，证实该分量为白噪声，可以剔除，将剩下的分量进行重构，达到去噪的目的。(The product of K EMD or LMD energy density and average cycle value when the K value was changed greatly, the component for white noise can be eliminated, the remaining components are reconstructed to achieve the purpose of de-noising.)