Monte_Carlo_evaluation

基于LMS算法的自适应噪声消除仿真分析,内含详细的文档说明(LMS-based adaptive noise cancellation algorithm simulation analysis, contains a detailed documentation)

利用matlab编程，从现有5种补货策略选取最优的策略，并对策略进一步优化。文件中包含问题的描述及优化过程。(The use of matlab programming, from the existing five kinds of replenishment strategy for selecting the optimal strategy, and strategy was further optimized. File contains a description of the problem and the optimization process.)

解线性方程组的直接法（标准数值算法），包括高斯消去法程序、列主元高斯消去法程序、LU分解以及用LU分解求线性方程组、Cholesky分解以及用Cholesky分解求线性方程组、改进的Cholesky分解以及用改进的Cholesky分解求线性方程组、解三对角方程的追赶法。全部为本人原创程序，且全部经过测试无误。共9个MATLAB程序。程序内部含详细注释。(Solving linear equations of the direct method (standard numerical algorithms), including Gaussian elimination procedure, the column pivot Gaussian elimination procedure, LU decomposition and the use of linear equations, LU decomposition, Cholesky decomposition, and find line with the Cholesky decomposition linear equations, Cholesky decomposition and improved using the improved Cholesky decomposition of linear equations, solution of tridiagonal equations pursuit method. All of my original program, and all tested correctly. A total of nine MATLAB. Internal procedures with detailed notes.)

奇异值分解；奇异值分解；奇异值分解；奇异值分解；奇异值分解；(Singular Value Decomposition Singular Value Decomposition Singular Value Decomposition Singular Value Decomposition Singular Value Decomposition Singular Value Decomposition)

toolbox for pattern recognition

基于Matlab的msk调制(Simulink文件）(Matlab based on the msk modulation (Simulink documentation))

说明：  对粒子滤波算法的原理和应用进行综述’首先针对非线性非高斯系统的状态滤波问题C阐述粒子滤波的原理D然后在分析采样=重要性=重采样算法基础上C讨论粒子滤波算法存在的主要问题和改进手段D最后从概率密度函数的角度出发C将粒子滤波方法与其他非线性滤波算法进行比较C阐明了粒子滤波的适应性C给出了粒子滤波在一些研究领域中的应用C并展望了其未来发展方向(QJPRQ Elc8&m :jelf dgwd99&jvdej gq:c&decwe 9d:ejv&chj&ec:d:cqi:pcrcw’8jfjgmdeelcg g&jgcd:"g g= #diqqjdghj&ec:9: u&cfCelcmcgc:jvjwcdq h9d:ejv&chj&ec:d:cmjpcgCudqcwgelcdgd&rqjqhqedgwd:wd&m :jelf=jf9 :edgvc=:cqdf9&jgmhj&ec:Celc9h9d:ev&chj&ec:d:cwjqviqqcwdgwqcjf9:d:cj&&iqe:decw)

我自己编写的用遗传算法寻找KSW最佳二维阈值，搞噪效果很好。(I prepared using genetic algorithm to find the best 2D Threshold KSW, engage in noise with good results.)

hidden markov models for face recegnisation

基于增广矩阵束的L型阵列的二维波达角估计(Beam based on the augmented matrix of two-dimensional array of L-type directe of arrival estimation)