junzhi

该程序是使用matlab语言编写的时钟，与北京时间完全相同(It is a clock compiled by matlab language.)

150例源码，提供学习和源码的分析实现！(150 cases of source code, to provide study and analysis of the implementation source code!)

This matlab file simulates CDMA system, Modulator and Demodulator modules are also available for download

读取数据库bnt文件,转换成为off文件(read bnt files)

程序实现了naive bayes classifier， 并附有对美国参议院根据投票情况来判断议员属于民主党还是共和党的例子。(Program achieved a naive bayes classifier, along with the U.S. Senate voting to determine under Democrat and Republican members belonging examples.)

卡尔曼滤波器的学习资料很不错的东西一起来学习吧(Kalman filter is a very good thing learning materials)

说明：  100个MATLAB程序，涉及数值分析、图形处理、界面设计、图形应用，稍加修改，即可套用。(100 MATLAB programs, involving numerical analysis, graphics, interface design, graphics, slightly modified, can be applied.)

This project is the I build to remote control my bulb at home.

（1）在MATLAB环境下编写FFT算法（不调用系统现有函数）； （2）实现对选定图片进行FFT计算、还原（IFFT计算），并与系统FFT函数做对比，进行分析； （3）设计GUI界面。((1) the preparation of the FFT algorithm (do not call the system existing function) in MATLAB environment (2) to achieve the selected image to the FFT calculation, reduction (IFFT computing), and FFT functions to do comparison with the system for analysis (3) Design GUI interface.)

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.)