Generate_Waveform_Agilent

Face Recognition Based on Polar Frequency Features

efficient transmit beamspace design for search-free based doa estimation in mimo radar

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)

This program is used for face recognition

The following Matlab project contains the source code and Matlab examples used for two stage kalman fliter for system identification. Reference :Lei Y, Jiang Y Q. The source code and files included in this project are listed in the project files section, please make sure whether the listed source code meet your needs there.

Round Numeric array element values to IEC 60063 (E-Series) component values.

matlab的无约束优化程序包，里面包括了课件，以及相关案例的源程序(Unconstrained Optimization matlab package, which includes courseware, as well as related case source)

该程序用matlab画出clarke模型下，信号理论自相关函数与仿真情况下自相关函数的情形对比。(The program with matlab draw clarke model, signal theory and simulation of the autocorrelation function of the autocorrelation function under the circumstances contrast.)

不同信噪比下的检测性能曲线，横轴信噪比，纵轴检测概率，随信噪比增加，检测概率提高。(Detection performance under different SNR curve)

波动方程正演模拟，交错网格二阶和四阶，和规则网格。适合新手学习。(Wave equation forward modeling, suitable for beginners to learn.)