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针对多径效应的影响，提出了一种基于矩阵束的MIMO 雷达低仰角快速估计方法。该方法同时考虑了发射多径信号和接收多径信号，采用单样本数信号矢量构造了一个前后向矩阵束，并利用两个酉矩阵对该矩阵束进行降维处理，最后采用广义特征值分解的总体最小二乘法来估计目标角度。算法不需要估计数据协方差矩阵，可在低 信噪比和单样本数情况下，有效地克服多径效应，实现同时多目标低仰角估计，相比最大似然算法，避免了谱峰搜索，计算量小。仿真结果验证了该算法的有效性。(To overcome the multipath effect, a fast algorithm for low elevation estimation for MIMO radar via matrix pencil is proposed. The signals both in transmit multipath and receive multipath are considered. Firstly, a forward-backward matrix pencil is formed based on the single-sampled vector. Secondly, the reduced-dimensional processing is applied to the matrix pencil via two unitary matrices. Finally, the generalized eigen-decomposition is employed to estimate the low elevation in multipath environments directly. Without the covariance matrix estimation, the proposed method can overcome multipath effect effectively in case of low SNR and estimate multi-target simultaneously. Compared with Maximum Likelihood (ML) method, it avoids spectrum peak searching and reduces the computational burden. Numerical results verify the effectiveness of this method)

非负矩阵分解的matlab代码，内容全！希望对大家有用(Non-negative Matrix Factorization of matlab code, the contents of the whole! Hope useful for everyone)

处理大规模矩阵，对大规模的矩阵进行分解，即形如分解A=UV(To deal with large-scale matrix, mass matrix decomposition, that is shaped like a decomposition A = UV)

计算机模拟和蒙特卡洛方法，文件格式为pdg,主要介绍随机模拟方法(Computer Simulation and the Monte Carlo method, file format pdg, stochastic simulation method introduced)

一维 问题，即激波管问题，是一个典型的一维可压缩无黏气体动力学问题，并有 解析解。对它采用二阶精度 两步差分格式进行数值求解。(Use MacCormack difference scheme for solving a two-dimensional shock tube problem)

计算给定序列的沃什(Walsh)变换序列。(Calculation of a given sequence of Vas (Walsh) transform sequence.)

说明：  统计学习经典教材，面试必备，详细介绍支持向量机、Boosting、最大熵、条件随机场等十个统计学习方法。(Classic textbooks for statistical study are essential for interviews)

说明：  三维FDTD程序,一个Fortran写的三维FDTD程序(Three-dimensional FDTD procedure, a Fortran program written by three-dimensional FDTD)

求函数极小值，适用于不带约束的、函数可以为非线性的无约束规划问题的求解(Demand function is minimum applicable to non-binding, the function can be non-binding for the non-linear programming problem solving)

支持向量机作为统计学习理论的实现方法，能很好地解决非线性和高维数问题，克服了神经网络方法收敛慢、解不稳定、推广性差的缺点，近年来得到了广泛地研究，在模式识别、信号处理、控制、通讯等方面得到了广泛地应用。(Support Vector Machine as the implementation of statistical learning theory approach, can be a good solution to the nonlinear and high dimension problem, the neural network method to overcome the slow convergence, solution instability, bad promotion of sexual shortcomings, in recent years has been widely studied, at pattern recognition, signal processing, control, communications, etc. has been widely applied.)