Geographic-data-analysis-Matlab

matlab的教程，例题，包括数值，符号，图像等运算及答案(matlab tutorials, sample questions, including the values, symbols, images and other computing and answers)

也是一个MATLAB编的计算器,功能比较强大,易于扩展(MATLAB is a series of calculators, and more powerful functionality, easy expansion)

这是一个非常重要的而又简单的程序，是书上常用和数学建模的好帮手( very good)

基于无速度传感器的异步电机调速系统，运用电流来合成磁链，控制方法是转子磁链定向。采用电流滞环控制，电网电压380V，转矩最大达30N.m。波形效果不错。(Based on speed sensorless induction motor speed control system, using current flux synthesis method for controlling the rotor flux orientation. Use current hysteresis control, grid voltage 380V, maximum torque of 30N.m. Waveform good results.)

说明：  一种关于图像阈值分割的算法，自己试过很好用。(An image threshold segmentation algorithm, I have tried it very well.)

Very good code for AM and FM modulation. For beginner

说明：  小波转换的简单例子小波转换的简单例子小波转换的简单例子(A simple example of wavelet transform Wavelet transform Wavelet transform a simple example of a simple example)

说明：  1.相关分析法辨识系统程序。2.方波响应与阶跃响应的互相转化的通用程序。3.获取系统模型阶次的函数。4.levy方法辨识系统的函数。5.将相关分析法的辨识结果转成频率响应的程序((1) analysis Identification System program. 2 square wave response and step response of the general program of mutual transformation. (3) for the function of the system model order. 4.levy method recognize the function of the system. The identification of the relevant analysis results converted to the frequency response of the program)

The MATLAB code which encrypt data based on AES technique.

基于最小二乘支持向量机理论,结合某风电场实测风速数据,建立了最小二乘支持向量机风速预测模型。对该风电场的风速进行了提前1h的预测,其预测的平均绝对百分比误差仅为8.55 ,预测效果比较理想。同时将文中的风速预测模型与神经网络理论、支持向量机(support vector machine,SVM)理论建立的风速预测模型进行了比较。仿真结果表明,文中所提模型在预测精度和运算速度上皆优于其他模型。 (Based on least squares support vector machine theory, combined with a wind farm measured wind speed data, the establishment of a wind vector machine forecasting model of least squares support. The velocity of the wind farm were predicted in advance 1h, the mean absolute percentage error of only 8.55 of its forecast, forecast effect is ideal. While the text of the wind speed forecasting models and neural networks, support vector machines (support vector machine, SVM) wind speed prediction models were compared with established theories. Simulation results show that our proposed model on prediction accuracy and computing speed are superior to other models.)