MATLAB7_0

这是一个关于MATLAB的很好的学习教程，包括了最基本的语法，怎样编程等很好。(It is a good learning MATLAB-tutorial, including the most basic grammar, how good programming.)

遗传算法，一种启发式算法，用于演化求最优值(Genetic algorithm, a heuristic algorithm for evolutionary optimization)

盲信号自然梯度法盲分离程序，用于进行瞬时盲分离(Natural Gradient Blind Signal Separation legal procedures, for instantaneous blind source separation)

用粒子群算法进行无功优化，比较实用，希望对大家有帮助(Particle swarm algorithm with reactive power optimization, more practical, we want to help, 14 nodes)

As the MAV propeller spins, it applies force to the air that passes through the propeller, increasing the momentum of the air while generating a thrust force on the MAV

Imperialist Competitive Algorithm

DMC预测控制matlab算法仿真实例，是自己选的一个控制系统区仿真(DMC predictive control algorithm matlab simulation examples)

MABC代码，为解决单目标优化问题,测试函数包括在其中(MABC code, for solving single objective optimization problem)

说明：  基于MATLAB的ASK编码，已经通过了MATLAB调试了(MATLAB-based ASK encoding, has adopted a MATLAB debugging)

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)