pca-fault

简单的神经网络学习规则赫布matlab代码。 这是不知情的初学者学生。它可应用于如简单的任务逻辑“和“，”或“，”不是“简单的图像和分类。 (Simple Matlab Code for Neural Network Hebb Learning Rule. It is good for NN beginners students. It can be applied for simple tasks e.g. Logic "and", "or", "not" and simple images classification.)

mitigation of sags and swells

This Matlab s code source contain a Spectrum Analyser

MATLAB 常用函数参考，对学校matlab学习帮助较大，快速掌握常用函数功能(MATLAB functions used for reference in school to learn matlab help large, frequently used functions quickly master the function of)

说明：  遗传算法工具箱，为英国谢菲尔德大学编写，在matlab7中通过(Genetic algorithm toolbox for the preparation of the University of Sheffield, by the matlab7)

小波三级非标准规格化分解与重构 将载入的图像文件显示并进行非标准haar小波规格化分解与重构过程(Normalized wavelet decomposition and reconstruction of three non-standard image file will be included in the non-standard display and haar wavelet decomposition and reconstruction process of normalization)

Related to Digital Image Processing

分析了支持向量回归机在能源需求预测中的优势,确定了输入向量集合和输出向量集合,建立了基于Matlab技术的SVR能源需求预测模型.对我国1985-2008年能源需求相关数据进行模拟与仿真,并对中国2010年和2020年能源需求量进行预测.研究结果表明:一是中国未来对能源的需求量逐渐增加,从2010年的330400万吨标准煤上升到2020年418320万吨标准煤,年均增长率为2.39％；二是在解决我国能源系统小样本.非线性及高维模式识别问题中SVR比BP神经网络等方法有更高的预测精度.(Support vector regression analyzes advantage in energy demand forecast to determine the set of input vectors and output vector set, established SVR energy demand forecasting model based on Matlab technology. Energy demand for our 1985-2008 related data modeling and simulation , and China in 2010 and 2020 energy demand forecast results show that: First, China s increasing demand for energy in the future, from 3.304 billion tons of standard coal in 2010 rose to 4.1832 billion tons of standard coal in 2020, average annual growth rate of 2.39 second is to solve our energy system small sample nonlinear and high dimensional pattern recognition problem SVR higher prediction accuracy than the BP neural network method.)

基于结构相似性的图像质量评价算法SSIM(Image quality assessment metric (Structural similarity index))

this is a simulation of current control of indirect drive please try it