Mathematical-modeling-

说明：  关于信号输入均匀量化器的信号幅度，用MATLAB实现量化过程(Uniform quantizer on the input signal amplitude, using MATLAB to quantify the process of achieving)

Thus file is a pdf. Explains discretization algorith CAIM for MAtlab

众所周知，欧拉角和四元数是存在对应关系的。后者用于导航等时不存在死区现象，而且，精度高，计算简单。(known, the Euler angles and quaternion is a correlation between them. Navigation for the latter did not exist at the Dead phenomenon, and with high accuracy, is simple.)

EM迭代算法源程序，可以应用到多用户检测中(EM iterative algorithm source code, multi-user detection)

matlab实现s小波变换代码,m文件。输入图像矩阵，输出一幅图像，分为四块。(s Matlab achieve wavelet transform code, m documents. Input image matrix, the output an image, divided into four.)

matlab code to convert image from 2d to 3d

An ideal SM control operates theoretically at an infi nite switching frequency so that the trajectory follows exactly the reference track

This is a source code for having echo effect in sound via DSP techniques

K最邻近密度估计技术是一种分类方法，不是聚类方法。 不是最优方法，实践中比较流行。 通俗但不一定易懂的规则是： 1.计算待分类数据和不同类中每一个数据的距离（欧氏或马氏）。 2.选出最小的前K数据个距离，这里用到选择排序法。 3.对比这前K个距离，找出K个数据中包含最多的是那个类的数据，即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering method. It is not the best method, but it is popular in practice. Popular but not necessarily understandable rule is: 1. calculate the distance between the data to be classified and the data in each other (Euclidean or Markov). 2. select the minimum distance from the previous K data, where the choice sorting method is used. 3. compare the previous K distances to find out which K data contains the most data of that class, that is, the class to which the data to be classified is located.)

分别采用4种控制律进行单神经元PID控制,即无监督的Hebb学习规则、有监督的Delta学习规则、有监督的Hebb学习规则、改进的Hebb学习规则.(Separately using four kinds of control laws for single neuron PID control, that is, unsupervised Hebb learning rules, there is the Delta Study supervision rules, there is supervised Hebb learning rule to improve the Hebb learning rule.)