edk91i_mb_ref_guide

this code is very good for TSOM

《MATLAB神经网络30个案例分析》中的第23个例子，案例23 小波神经网络的时间序列预测-短时交通流量预测。希望对大家有一定的帮助！(The MATLAB neural network analysis of 30 cases of 23 example, 23 cases of wavelet neural network time series forecasting- short-term traffic flow prediction. Hope to have certain help to everybody! )

Direct Torque Control System！！！Direct Torque Control SystemDirect Torque Control System(Direct Torque Control System! ! ! Direct Torque Control SystemDirect Torque Control System)

Matlab 实现zernike矩的计算(compute zernike moment in matlab)

采用一种松弛牛顿法，对IEEE33节点系统进行潮流计算，并得出正确结果。(Newton s method uses a relaxation programming for IEEE33 node system and derive the correct results)

photovoltaic characteristics Simulink model of photovoltaic cellule

编写程序完成不同滤波器的图像频域降噪和边缘增强的算法并进行比较，得出结论,效果很好，多种方法工你选择，文档中包含图片( Image Frequency noise reduction and edge enhancement algorithms to program completion and compare different filters, concluded that the effect is very good, work a variety of methods to choose from, the document contains a picture)

Matlab图像处理中常用的canny码源(This is canny code)

this file contains Matlab code for calculating the snr of mmse equalizer

This tutorial is designed to give the reader an understanding of Principal Components Analysis (PCA). PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding patterns in data of high dimension. Before getting to a description of PCA, this tutorial first introduces mathematical concepts that will be used in PCA. It covers standard deviation, covariance, eigenvectors and eigenvalues. This background knowledge is meant to make the PCA section very straightforward, but can be skipped if the concepts are already familiar.