foc

BPSK_BER_GAIN_OFDM Phase Shift Keying

this is image frequency transform,vevr good(This is the image frequency transform, vevr good)

产生宽带QPSK信号，并通过rrc滤波，用于检验发射通路的EVM等指标(Produce wideband QPSK signals, and by rrc filter, used to test the emission path of EVM and other indicators)

MATLAB符号积分变换经典教程MATLAB Tutorial classic symbol integral transformation(MATLAB symbolic integral transform classical tutorial MATLAB Tutorial classic symbol integral transformation)

阵列信号中虚拟变换的程序，主要对MVDR进行了虚拟变换进行仿真，很好用。(Array signal the virtual transformation process)

灰色预测模型称为CM模型，G为grey的第一个字母，M为model的第一个字母。GM（1，1）表示一阶的，一个变量的微分方程型预测模型。GM（1，1）是一阶单序列的线性动态模型，主要用于时间序列预测。 一、GM（1，1）建模 设有数列 共有 个观察值 对 作累加生成，得到新的数列 ，其元素 （5-1） 有： 对数列 ，可建立预测模型的白化形式方程， （5-2） 式中： ——为待估计参数。分别称为发展灰数和内生控制灰数。设 为待估计参数向量 则 按最小二乘法求解， 有： （5-3） 式中： （5-4） （5-5） 将（5-3）式求得的 代入（5-2）式，并解微分方程，有 （1，1）预测模型为： （5-6）(gray forecasting model called CM model, the G-gray of a letter, the M model for the first letter. GM (1,1), a band of a variable type of differential equation models. GM (1,1) is a sequence of single-band linear dynamic model, mainly for time series prediction. A GM (1,1) model series with a total value of observation for the cumulative production, to a new series of its elements (5-1) : The series, we can establish the prediction model albino form of equation (5-2) where :-- to question the estimated parameters. The development will be known as the gray and hygiene control within a few gray. Set parameters to be estimated according to Vector least squares method, are : (5-3) where : (5-4) (5-5) (5-3) that obtained in lieu of income (5-2)- and solutions differential equations, (1 1) Fore)

说明：  四阶Runge-kuta求解算法matlab代码 含一篇文献介绍(Fourth-order algorithm lunge-kuta)

该程序设计简单，计算结果准确。能很好的利用该程序给出二维光子晶体的禁带结构(the design process simple and accurate. Can be a very good use of the program is two-dimensional photonic crystal structure of the forbidden zone)

模拟退火算法matlab实例，介绍了matlab的算法的具体使用方法(Simulated annealing algorithm matlab example, introduced the specific use of Matlab algorithm)

Randon Variables,expectation value, Gaussian distributions, white Nosie, probability density