eeglab

说明：  遗传算法 求解单目标问题，采用二进制编码（matlab)(using genetic algorithm to optimize Single-objective function)

说明：  在matlab中实现时间抽取基2 FFT算法(Matlab achieve in the time taken from the base 2 FFT algorithm)

matlab中的Rayleigh信道模型，基于基于Clarke模型的Jakes仿真器(matlab in the Rayleigh channel model, Jakes simulator based on Clarke Model)

auditry feture xtrction

unit commitment problem

2D-LAD demensionality reduction matlab

用趋近律方法设计的滑膜控制器算法例程，模型对象为G(s)=133/s(s+25).(Reaching law designed by synovial controller algorithm routines, model objects for the G (s) = 133/s (s+25).)

求解legendre多项式的系数，N各点对应N阶legendre多项式，有N+1各多项式系数，采用递推公式，40阶后误差较大。(Solving legendre polynomials, N points corresponding to N-order legendre polynomial, there are N+1 coefficients of the polynomial, using recursive formulas, after the error of order 40 more.)

应用支持向量机回归和相空间重构对时间序列进行预测(Support vector machine regression and time series phase space reconstruction on forecast)

说明：  共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(The Conjugate Gradient method is a method between the steepest descent method and the Newton method. It only needs to use the first derivative information, but overcomes the shortcomings of the steepest descent method and avoids the need for the Newton method to store And the calculation of Hesse matrix and the inverse of the shortcomings, conjugate gradient method is not only to solve large-scale linear equations one of the most useful methods, but also solution for large-scale nonlinear optimization of one of the most effective algorithm. In a variety of optimization algorithms, conjugate gradient method is a very important one. The advantage is that the required storage capacity is small, with step convergence, high stability, and does not require any external parameters.)