LWOA

根据具体数值计算在匀强磁场中旋转导体棒的电动势，用动画演示导体棒在磁场中的旋转。(According to the electromotive force of the specific numerical calculation conductor rod rotates in a uniform magnetic field, animation conductor rod in a magnetic field rotation.)

交织程序。信道编码的交织。用于序列的交织与解交织。也可用于交织的盲检测。(Mixed program.Channel coding intertwined.Interweave and solution used in sequence.Blind detection can also be used for weaving.)

有向无环图支持向量(DAG-SVMS)多类分类方法,是一种新的多类分类方法。该方法采用了最小超球体类包含作为层次分类依据。试验结果表明,采用该方法进行多类分类,跟已有的分类方法相比有更高的分类精度。 (Directed acyclic graph support vector (DAG-SVMS) multi-category classification methods, is a new multi-category classification methods. The method uses the smallest category of super-sphere that contains the level of classification as a basis. The experimental results show that using the method of multiclass classification with the classification method has been compared to a higher classification accuracy.)

光子筛孔均匀分布的例程，用于光子筛成像时使用(Uniform distribution of photon sieve routines for use imaging photon sieve)

color detection using matlab by image processing

利用matlab中simulink进行蓝牙扩频通信系统的仿真，研究其的性能。( Bluetooth FM communication system are simulated with the use of matlab/simulink, and study the performance of the system )

UILDING THERMAL PERFORMANCE ANALYSIS BY USING MATLAB/SIMULINK

线性调频信号的脉冲压缩，合成孔径雷达(SAR)的第一个作业程序(the compression of chirp signal)

ecently, more and more attention is paid to reversible data hiding (RDH) in encrypted images, since it maintains the excellent property that the original cover can be losslessly recovered after embedded data is extracted while protecting the image content’s confidentiality. All previous methods embed data by reversibly

正交最小二乘辨识算法 该算法除了实现最小二乘辨识功能之外而且能按照各项重要性将其逐一选出并且估计相应系数(OLS Orthogonal Least Quares. [x, ind] = OLS(A,b,r) gives the solution to the least squares problem using only the best r regressors chosen from the ones present in matrix A. This function also returns in the vector ind the indexes of the best r regressors (i.e., the best columns of A to use). If r is equal to n, the solution x given by OLS is the same as the solution given by A, but in ind we still have the regressors sorted by their importance. This means that one can perform a feature selection by taking the first k entries in ind (k<r).)