NEWwavelet

Bayes program 贝叶斯的课程设计，报告搜索bayes(Bayes Bayes program curriculum design, report search bayes)

《精通MATLAB GUI设计（第2版）》的源程序(MATLAB GUI)

说明：  该程序可以生成WVD分布，将其做成函数可以方便研究员做研究使用。(it can generate the WVD function.)

分布估计算法，是一个数据包，能实现群的一般算法(Distribution estimation algorithm, which is a packet, can achieve the group of the general algorithm )

matlab模糊k-means聚类算法源码，很实用，略微改造即可使用(matlab fuzzy k-means clustering algorithm source code, very practical, you can use a little renovation)

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)

用Matlab编写可一个可看的时钟模拟器，指针形式不是数值形式。(Using Matlab to write a simulator to see the clock, not the form of a pointer value in the form.)

说明：  传感器阵列波束优化设计与应用书籍的第五章natlab程序(Chapter 5 matlab program of book Sensor array beam optimization design and application)

内模控制器（IMC）工具箱。包括参数整定、PID控制器参数转换等 (Internal Model Control（IMC） toolbox。parameter tunning and PID controller parameters transvering,etc)

2D FDTD realization with Near-to-Far field transformation