statespacemodel1

matlab的另一个功能就是应用在图像处理上。有强大的能力处理图像。希望对读者有很大的帮助(Another feature is the application of matlab in image processing. Has a strong ability to handle images. Hope to be very helpful to readers)

in this code i have implemented the algorithm to find the minimum sampling frequency bandpasss sampling used in Software defined radio

DRROBOT I90的基本應用以及智慧型影像錄相機無線移動系統(The basic application DRROBOT I90, and intelligent video recorder wireless mobile systems)

正交相移键控 (Quadrature Phase Shift Keying)简称“QPSK”，是一种数字调制方式。它分为绝对相移和相对相移两种。由于绝对相移方式存在相位模糊问题，所以在实际中主要采用相对移相方式DQPSK。目前已经广泛应用于无线通信中，成为现代通信中一种十分重要的调制解调方式。(QPSK THAT IS TO SAY....)

Daubechies小波基的构造 采用双尺度方程求解小波基函数(The Daubechies wavelet construct two-scale equation solving wavelet function)

说明：  mpsk的调试源程序，详细介绍了整个调制的过程和源码分析(mpsk debugging source code, detailing the entire process and source of modulation)

三个程序,分别以四阶龙格库塔法和欧拉法解洛伦兹方程,并绘制相图,时间演化图,庞加莱截面图.(Three procedures, respectively, fourth-order Runge-Kutta method and Euler method for solving the Lorentz equation and draw the phase diagram, the time evolution of the map, Poincare section.)

用matlab编写的经典电力系统经济调度程序。(this is a program for power system economic emission dispatch considering the network loss。 )

is for smulation of Induction Motor using MATLAB

说明：  按FPE定阶的 源程序：fpe.cpp M序列：M序列.txt 白噪声：Gauss.txt 程序中先用依模型阶次递推算法估计模型的参数，再用fpe方法判断模型的阶次。 程序运行结果如下： n: 1 判断阶次FPE的值: 0.0096406 -0.481665 1.07868 n: 2 判断阶次FPE的值: 0.00875755 -0.446739 0.00498181 1.07791 0.0527289 n: 3 判断阶次FPE的值: 0.0087098 -0.459433 0.120972 -0.0569228 1.07814 0.0390757 0.116982 n: 4 判断阶次FPE的值: 0.000396884 -0.509677 0.4501 -0.200906 0.0656188 1.07991 -0.0156362 0.442989 0.0497236 n: 5 判断阶次FPE的值: 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771 n: 6 判断阶次FPE的值: 3.23349e-007 -1.14659 0.76933 -0.487651 0.329676 -0.10377 -0.00440907 1.07999 -0.703574 0.447253 -0.235282 0.113587 0.00479688 从以上结果可以看出，当n=5时，fpe值最小，所以这时的模型阶次和参数估计值为最优结果： 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771(err)