JOURNAL-bear

粒子滤波程序，仿真实现自由度机器人对目标的跟踪，使用kalman滤波估计总雅可比矩阵J，噪声为非高斯噪声(Particle filter procedure, simulation robot tracking of targets, the use of kalman filter estimated total Jacobian matrix J, the noise of non-Gaussian noise)

很好的东西，关于用卡尔曼算法做对消算法的...(Good things Kalman algorithm cancellation algorithm ...)

说明：  数值分析中运用matlab使用LU分解法求线性方程组(Numerical analysis using matlab LU decomposition method for solving linear equations)

扩展年有限元的相关文献，内含7篇综述，完整概括扩展有限元的发展。做这个方面的可以看一看。(Extended Finite element of the relevant literature, containing 7 review, complete the development of finite element summed expansion. So this area can take a look.)

基于Ansys有限元软件，利用MPC技术对SOLID-SHELL单元进行连接实例—简支梁(Based on Ansys finite element software, the use of MPC SOLID-SHELL unit connected instance- Charpy)

用于处理信号，对信号进行小波包分解，此处进行了三层分解计算，可以进行迭代。(Used to process the signal, the wavelet packet decomposition of the signal, where the three-tier decomposition of the calculation can be iterated.)

python机器学习预测分析核心算法的例程(Python machine learning prediction and analysis of core algorithm routines)

说明：  非常好的卡尔曼滤波学习程序。文章中有原题，有解题步骤，有实现程序。适合卡尔曼学习过程中的人。(Very good learning process Kalman filter. The article in the original title, there are problem-solving steps to achieve the procedure. Kalman learning process for people.)

gmres 方法。视图求解线性方程组A*x=b的解x。nXn的稀疏矩阵A必须是方程且应是大型稀疏矩阵。列向量b的长度必须为n。(gmres method. View solving linear equations A* x = b the solution x. nXn sparse matrix A must be equation and should be large sparse matrix. The length of the column vector b must be to n.)

说明：  包括我自己写的一些数值分析用到的函数 包括矩阵的LU分解的两种方法, Cholesky分解, 以及线性方程组的迭代解法中的雅克比, 高斯-赛德尔以及线性松弛法的函数(Including myself, used to write some of the numerical analysis functions, including matrix LU decomposition of two methods, Cholesky decomposition, and iterative solution of linear equations in the Jacobi, Gauss- Seidel and linear relaxation method function)