package_emd

MATLAB中文帮助.chm 如果你是MATLAB的初学者，你应该从阅读矩阵操作开始。最重要的是要学习如何输入矩阵，如何使用：（冒号）算子，以及如何调用函数。 在你掌握了基础之后，你应该阅读其他章节并运行实例。(MATLAB Chinese help. Chm If you are a MATLAB beginner, you should read the matrix from the start operation. The most important thing is to learn how to enter the matrix, how to use: (colon) operator, and how to call the function. You mastered the basic, you should read the other sections and run the examples.)

说明：  MATLAB的一个学习资料，pdf格式 不是图片扫描的所以说比较清楚(MATLAB)

分布傅里叶计算孤子程序，单孤子以及多孤子相互作用均可用次程序(soliton programe)

无迹卡尔曼滤波，摒弃了对非线性函数进行线性化的传统做法，采用卡尔曼线性滤波框架，对于一步预测方程，使用无迹(UT)变换来处理均值和协方差的非线性传递，就成为UKF算法(Unscented Kalman filter, eliminating the linearization of the nonlinear function of the traditional practice of using a linear Kalman filter framework for further prediction equation, using unscented (UT) transformation to handle nonlinear transfer mean and covariance, it become UKF Algorithm)

永磁直驱风力发电机，并网机侧部分matlab仿真研究(permanent magnel direct drive wind tuibine grid connected inverter side part)

说明：  根据掺镱光纤激光器的速率方程，对激光器工作进行仿真(According to the ytterbium doped fiber laser rate equations，simulate the laser‘s working)

主要实现可倾瓦轴承轴承油膜压力计算，文件包括雷诺方程的差分求解的理论推导和matlab实现代码。(The main achievement tilting pad bearings film pressure calculations, including the theory of differential file solving the Reynolds equation is derived and matlab implementation code.)

These files contain all the code necessary to run the example in the Webinar "Signal Processing for Machine Learning in MATLAB". They also include code to automate the download and preparation of the dataset used. In that webinar we presented an example of a classification system able to identify the physical activity that a human subject is engaged in, solely based on the accelerometer signals generated by his or her smartphone. We used consolidated signal processing methods to extract a fairly small number of highly-descriptive features, and finally trained a small Neural Network to map the feature vectors into the 6 different activity classes of a pre-recorded dataset. The topics discussed include: * Signal manipulation and visualisation * Design and application of digital filters * Frequency-domain analysis * Automatic peak detection * Feature extraction from signals * Train and test of simple Neural Networks

单级移动倒立摆建模及串连滞后校正 自动控制课程设计(Single-stage mobile inverted pendulum model and serial lag correction curriculum design automation)

用matlab编程实现p-m方程的源代码(Programming using matlab source code pm equation)