mo-hinh-hoa

global posistioning system ,the different types of antenna used

说明：  多类划分 matlab中使用数据挖掘的实例一个 方便新人参考(Matlab data mining multi-class classification)

basic operations on an image like negative, log

16信道化合成matlab仿真，基于一种新的方式，非杨小牛书上的那种，并且易于FPGA实现(16 channel combined into the matlab simulation, based on a new way, the Yang books of that kind of, and easy to FPGA implementation )

说明：  基于MATLAB/GUI的M-QAM调制解调及误码率,本文件是在MATLAB2009a版本上设计的，低于此版本的有可能会出错。 此文件中“M_QAM.m”是主文件，其他均为调用文件,该程序实现了MQAM的调制解调功能，并画出了每一步的波形 (Based on MATLAB/GUI s M-QAM modulation and demodulation and bit error rate, this document is designed MATLAB2009a version, this version is lower than might be wrong. This file is in the " M_QAM.m" is the main document, others are calling the file, the program implements the MQAM modulation and demodulation functions, and draw the waveform of each step)

this is programm for propagation that can help you to solve the case in propagation and transmission media fron transmitter to receiver. we can count link budget in propagation.

MATLAB信号系统教程含源码测试通过 复制代码到.m文件即可 (MATLAB Signal System tutorials with source code to the test by copying. M files can)

POD本征正交分解POD本征正交分解POD本征正交分解POD本征正交分解(POD POD proper orthogonal decomposition of the orthogonal decomposition POD proper orthogonal decomposition POD of the orthogonal decomposition)

DMI WITH N EQUAL TO 4,8,20

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.)