matlab

program in matlab code to do a equalization of a signal DSP Applications

扩展的kalman 滤波算法，使用matlab进行实现,由国外人士编写(Extended kalman filter algorithm, using matlab to achieve)

鲍威尔算法的matlab实现，鲍威尔算法是直接利用函数值来构造共轭方向的一种方法(Powell algorithm matlab realize)

Markov Chain Monte Carlo and gibbs sampling

说明：  电力系统无功优化相关，基于粒子群优化算法的电力系统无功优化设计(Power system reactive power optimization)

simulation psk, simulation source, there are descriptions and explanations related to procedures and functions are.

说明：  一个用来计算一维光子晶体全息干涉分布的程序，很好用的！(Used to calculate a one-dimensional photonic crystal holographic interferometry distribution procedures, very good use!)

自适应（LMS）算法在噪声抑制中的应用。在仿真中，原始信号选为sin((0.2*pi)*t), 噪声信号采用标准白噪声，延迟D=1，收敛因子分别是u=0.001和u=0.3(Adaptive (LMS) algorithm in noise suppression application. In the simulation, the original signal is selected sin ((0.2* pi)* t), noise signal using the standard white noise, the delay D = 1, respectively, convergence factor u = 0.001 and u = 0.3)

梯度下降法是最早最简单，也是最为常用的最优化方法。梯度下降法实现简单，当目标函数是凸函数时，梯度下降法的解是全局解。一般情况下，其解不保证是全局最优解，梯度下降法的速度也未必是最快的。梯度下降法的优化思想是用当前位置负梯度方向作为搜索方向，因为该方向为当前位置的最快下降方向，所以也被称为是”最速下降法“。最速下降法越接近目标值，步长越小，前进越慢。(The gradient descent method is the earliest and most simple and most commonly used optimization method. The gradient descent method is simple to realize. When the objective function is a convex function, the solution of the gradient descent method is a global solution. In general, the solution is not guaranteed to be the global optimal solution, and the gradient descent method is not necessarily the fastest. The optimization idea of gradient descent method is to use the current position negative gradient direction as the search direction, because the direction is the fastest descending direction of the current position, so it is also called the steepest descent method. The faster the slowest descent approach is closer to the target, the smaller the step, the slower the progress.)

用db4小波分解六层：s=a6+d6+d5+d4+d3+d2+d1(db4 wavelet decomposition of six layers: s = a6+ d6+ d5+ d4+ d3+ d2+ d1)