chuanxingbuhuo

信号功率谱密度、信道为AWGN信道时构造一种接收机(Signal power spectral density, for the AWGN channel when the channel construct a receiver)

IN highly scattered enviroment，the Capacity of a MIMO channel with nt transmit antenna and nr recieve antenna is analyzed. The power in parallel channel (after decomposition) is distributed as water-filling algorithm(IN highly scattered enviroment, the Capacity of a MIMO channel with nt transmit antenna and nr recieve antenna is analyzed. The power in parallel channel (after decomposition) is distributed as water-filling algorithm)

已知赤经赤纬计算轨道六根数，采用高斯算法(calculate orbit elements（gauss))

1.duishuzhengtai：产生对数正态分布 2.gaussian：产生数据量为n的两个相互独立高斯分布y1、y2 3.junyun：自定义 0-1的均匀分布，n代表数据量，一般要大于1024（蒙特卡罗） 4.ruili：瑞利分布,m是瑞利分布的参数,n代表数据量,n一般要大于1024 5.kaifeng：产生开丰分布，其中m代表开丰分布的自由度，n表示产生的点数量 6.tfenbu：本函数产生自由度为m，数据量为n的t分布。 7.weibuer：a=1时,是指数分布；a=2时,是瑞利分布(1.duishuzhengtai: generating lognormal 2.gaussian: generating a data quantity n of two mutually independent Gaussian distribution Y1, Y2 3.junyun: custom uniform distribution of 0-1, n represents a data amount, generally large in 1024 (Monte Carlo) 4.ruili: Rayleigh distribution, m is a parameter of the Rayleigh distribution, n representative of the amount of data, n is generally greater than 1024 5.kaifeng: generating open abundance distribution, wherein m represents an open-abundance distribution freedom of degrees of freedom, n is the number of points generated 6.tfenbu: This function generates m, the amount of data for n t distribution. 7.weibuer: a = 1, the exponential distribution a = 2, is a Rayleigh distribution)

fuzzy identification

Matlab教训，PPT格式，从入门到精通。(Matlab lessons, PPT format, from entry to the master.)

说明：  灰色模型程序，自己编的，如有错误请大侠指点。(Gray model program, their own series, if any error please heroes pointing.)

用matlab对FIR滤波器进行仿真，得到其特性曲线(Of FIR filter using matlab simulation, by its characteristic curve)

层次分析法的自动实现算法基于matlab，代码如文件(Automatic algorithm based on the Analytic Hierarchy Process matlab, code such as file)

A matlab implementation of the KNN classifier. It is tested and working well.