pinlv

非常好的MATLAB学习书籍，图像处理.非常值得下载，一定能对用户有很大帮助。(A very good book to learn MATLAB, image processing. Well worth downloading certainly of great help to users.)

说明：  图像降维方法pca和kpca的matlab程序(Image dimensional reduction pca and kpca the matlab program)

matlab实现图上需找最短路径的迪杰斯特拉算法，寻找任一点和其他点之间的最短距离，最终结果为最短路径度量矩阵和正序路由矩阵(matlab implementation on the map to find the shortest path Dijkstra algorithm to find the shortest distance between any point and other points, the final result is the shortest path metric matrix and positive sequence routing matrix)

it is matlab m file

matlab的90个应用实例源代码，欢迎交流(The 90 matlab source code application examples are welcome to exchange)

This is the m file to read or uff file using matlab, uff file to generate. It is sometimes convenient to issue read, create, so that if someone put a data value.

ICP 改进的ICP 点云拼接 有chen 等人的改进版(Improved ICP Demo of Range Image Registration Techniques)

说明：  基于matlab 的 iir高通滤波器设计，可以过滤150Hz以下的噪声；使用时把音频路径替换正自己的音频路径即可运行。(The design of IIR high pass filter based on Matlab can filter the noise below 150Hz; when using, the audio path in the file can be changed to its own path to run)

V2V simulation vehicle to vehicle communication(vehicle to vehicle communication based on random sourcing, urban & highway situation)

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.)