Python-GUI-Programming-using-Tcl[1]

说明：  粗糙集属性约简，包括正域的计算，约简结果的提取(Rough Set Attribute Reduction, including the calculation of positive fields, the extraction of reduction results)

说明：  通过em算法实现对数据的高斯混合模型的分类(Em algorithm through implementation of data Gaussian mixture model classification)

电力系统短路故障计算 ，应用于电力系统分析。(Power system fault calculation)

数字信号处理关于数字滤波器的设计，并用matlab实现(Digital signal processing on the digital filter design and realization of matlab)

说明：  matlab 的一本书的光盘，我们学校一直用这个，大家反映很好(matlab a book of CDs, our school has been using this, we reflect the very good)

基于特征向量约束的波束形成算法例程，老外写的，对于多种波束形成算法的阵列增益等参数进行了详细的比较。(An beamforming example using feature vector constrain.)

智能电梯系统仿真用matlab程序实现，智能控制(ntelligent elevator system simulation)

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.)

使用改进的Nyquist脉冲实现OFDM信号的PAPR抑制(Nyquist pulse PAPR)

matlab设计，有助于学习simulink知识(matlab design knowledge to help learning simulink)