examples

qpsk程序对刚入门的同学或者朋友，有着很大的帮助。(Delayed entry program for students or just friends, a great help.)

有关分数阶离散傅里叶变换的程序以及文章，文章详细介绍了离散傅里叶变换，有助于读者的学习(Fractional Fourier transform on the procedures and articles, the article introduces the discrete Fourier transform, to help readers learn)

一种基于自适应按需加权分簇算法的CBRP路由协议研究(Based on adaptive on-demand weighted clustering algorithm for routing protocol research CBRP)

说明：  W-矩阵置乱，效果比Arnold置乱更好(W-matrix scrambling, it is better than Arnold)

MIMO OFDM 2发2收通过simulink实现的基本链路(MIMO OFDM 2 2 admission made by Simulink achieve the basic link)

小车的8字绕环，小车的机械结构设计相关尺寸计算，运用MATLAB计算(8 words circling the car, the car' s mechanical design calculations relevant dimensions, calculated using MATLAB)

说明：  最速下降法是迭代法的一种,可以用于求解最小二乘问题(线性和非线性都可以)。在求解机器学习算法的模型参数，即无约束优化问题时，梯度下降（Gradient Descent）是最常采用的方法之一，另一种常用的方法是最小二乘法。在求解损失函数的最小值时，可以通过梯度下降法来一步步的迭代求解，得到最小化的损失函数和模型参数值。反过来，如果我们需要求解损失函数的最大值，这时就需要用梯度上升法来迭代了。在机器学习中，基于基本的梯度下降法发展了两种梯度下降方法，分别为随机梯度下降法和批量梯度下降法。(The steepest descent method is a kind of iterative method, which can be used to solve the least squares problem (both linear and nonlinear). In solving the model parameters of machine learning algorithm, that is, unconstrained optimization, gradient descent is one of the most commonly used methods, and the other is the least square method. When solving the minimum value of loss function, the gradient descent method can be used step by step to get the minimum value of loss function and model parameters. Conversely, if we need to solve the maximum value of the loss function, then we need to use the gradient rise method to iterate. In machine learning, two kinds of ladders are developed based on the basic gradient descent method)

China stock data format. fit to programmer

预测控制单变量控制以及改变MＰ等参数变化下曲线控制matlab,包括多变量等控制(Curve control matlab under the predictive control univariate control and change the P parameter changes)

包括emd分解程序，求边际谱程序，hilbert包络解调程序，求取小波包频带能量程序，K均值聚类程序(fault diagnosis program)