十种概率密度函数

一十种概率密度函数functionzhifangtu(x,m)%画数据的直方图,x表示要画的随机数,m表示所要画的条数%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%a=min(x);b=max(x);l=length(x);h=(b-a)/m;%量化xx=x/h;x=ceil(x);w=zeros(1,m);fori=1:lforj=1:mif(x(i)==j)%x(i)落在j的区间上，则w(j)加1w(j)=w(j)+1;elsecontinueendendendw=w/(h*l);z=a:h:(b-h);bar(z,w);title('直方图')functiony=junyun(n)%0-1的均匀分布，n代表数据量，一般要大于1024%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%y=ones(1,n);x=ones(1,n);m=100000;x0=mod(ceil(m*rand(1,1)),m);x0=floor(x0/2);x0=2*x0+1;u=11;x(1)=x0;fori=1:n-1x(i+1)=u*x(i)+0;x(i+1)=mod(x(i+1),m);x(i)=x(i)/m;end%x(n)单位化x(n)=x(n)/m;y=x;functiony=zhishu(m,n)%指数分布,m表示指数分布的参数,m不能为0.n表示数据量,n一般要大于1024%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%x=junyun(n);fori=1;nif(x(i)==0)x(i)=0.0001;elsecontinue;endendu=log(x);y=-(1/m)*u;functiony=ruili(m,n)%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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%x=junyun(n);fori=1:nif(x(i)==0)x(i)=0.0001;elsecontinue;endendu=(-2)*log(x);y=m*sqrt(u);functiony=weibuer(a,b,n)%韦布尔分布,a,b表示参数,b不能为0.n表示数据量,一般要大于1024%a=1时,是指数分布%a=2时,是瑞利分布%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%x=junyun(n);fori=1:nif(x(i)==0)x(i)=0.0001;elsecontinue;endendu=-log(x);y=b*u.^(1/a);functiony=swerling(n)%swelingII分布%%%%%%%%%%%%%%%%%%%%%%r=ones(1,n);u=junyun(n);v=junyun(n);fori=1:nif(u(i)==0)u(i)=0.0001;elsecontinueendendfori=1:nif(u(i)==v(i))u(i)=u(i)+0.0001elsecontinueendendt=-2*log(u);h=2*pi*v;x=sqrt(t).*cos(h);z=sqrt(t).*sin(h);y=(r/2).*(x.^2+z.^2);functiony=bernoulli(p,n)%产生数据量为n的贝努利分布,其中p属于(0-1)之间。%-----------------------%u=junyun(n);y=zeros(1,n);fori=1:nif(u(i)=p)y(i)=1;elsey(i)=0;endendfunctiony=duishuzhengtai(a,b,n)%产生对数正态分布，a,b为随机分布的参数，n为数据量%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%x=gaussian(n);u=sqrt(b)*x+a;y=exp(u);functiony=kaifeng(m,n)%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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%y=zeros(1,n);if(floor(m/2)==m/2)fori=1:m/2[x1,x2]=gaussian(n);forj=1:ny(j)=x1(j)^2+x2(j)^2+y(j);endendelsefori=1:floor(m/2)[x1,x2]=gaussian(n);forj=1:ny(j)=x1(j)^2+x2(j)^2+y(j);endendx=gaussian(n);forj=1:ny(j)=y(j)+x(j)^2;endendfunctiony=dajiama(a,b,n)%产生伽马随机分布的数据，a、b为随机分布的参数，数据量为n%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%k=1;if(a1)while(k=n)x1=junyun(1);x2=junyun(1);y2=(exp(1)+a)/exp(1)*x2;if(y21)p=-log(((exp(1)+a)/exp(1)-y2)/a);if(x1p^(a-1))y(k)=p;k=k+1;elsecontinue;endelsep=y2^(1/a);if(x1exp(-p))y(k)=p;k=k+1;elsecontinue;endendendelseif(a=1)while(k=n)x1=junyun(1);x2=junyun(1);v=(2*a-1)^(-0.5)*log(x1/(1-x2));x=a*exp(v);z=x1^2*x2;w=a-log(4)+(a+sqrt(2*a-1))*v-x;if(w=log(z))y(k)=x;k=k+1;elsecontinue;endendendy=b*y;functiony=beitafenbu(a1,a2,n)%产生贝他分布的随机数，其中a1、a2是贝他分布的参数，n代表数据量%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%x1=dajiama(a1,1,n);x2=dajiama(a2,1,n);y=x1./(x1+x2);function[y1,y2]=gaussian(n)%产生数据量为n的两个相互独立高斯分布y1、y2%---------------------------------------%k=1;y1=zeros(1,n);y2=zeros(1,n);while(k=n)u1=junyun(1);u2=junyun(1);v1=2*u1-1;v2=2*u2-1;s=v1^2+v2^2;if(s=1)continue;elseif(s==0)k=k+1;elsey1(k)=v1*sqrt(-2*log(s)/s);y2(k)=v2*sqrt(-2*log(s)/s);k=k+1;endendfunctiony=canshu(x);y=ones(1,2);n=length(x);y(1)=sum(x)/n;z=x-y(1);z=z.^2;y(2)=sum(z)/(n-1);functiony=correlation(x)%计算x的自相关函数%%%%%%%%%%%%%%%%%%%%%%%%%n=length(x);fori=1:nx1(i)=x(n+1-i);endy=conv(x,x1);二．三种相关杂波functiony=gaussianpu(x)%由数据量为n的高斯白噪声产生向量为n，功率谱为高斯型的高斯随机向量%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%N=0:20;f=20;T=1/256;c=2*f*T*sqrt(pi)*exp(-4*f^2*pi^2*T^2*N.^2);n=length(x);y=zeros(1,n);fork=1:nfori=20:-1:0if((k-i)=0)continue;elsey(k)=y(k)+c(21-i)*x(k-i);endendfori=20:40if((k-i)=0)continue;elsey(k)=y(k)+c(i-19)*x(k-i);endendendy=0.5*y;functiony=weibuerpu(a,b,n)%由数据量为n的高斯白噪声产生向量为n，功率谱为高斯型的韦布尔分布的随机向量%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%[z1,z2]=gaussian(n);z1=5*z1;z2=5*z2;y1=sqrt(b^a/2)*z1;y2=sqrt(b^a/2)*z2;x1=gaussianpu(y1);x2=gaussianpu(y2);x1=sqrt(b^a/2)*x1;x2=sqrt(b^a/2)*x2;y=x1.^2+x2.^2;b=canshu(y);y=y-b(1);functiony=duishuzhengtaipu(a,b,n)%由数据量为n的高斯白噪声产生向量为n，功率谱为高斯型的对数正态随机向量%a表示标准方差,b表示均值%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%z1=gaussian(n);x=gaussianpu(z1);y=a*x;y=exp(y);y=b*y;b=canshu(y);y=y-b(1);%去掉直流分量functiony=swerling2pu(n)%由数据量为n的高斯白噪声产生向量为n，功率谱为高斯型的斯维凌II型随机向量%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%r=6;[z1,z2]=gaussian(n);x1=gaussianpu(z1);x2=gaussianpu(z2);y=x1.^2+x2.^2;y=r*y;b=canshu(y);y=y-b(1);%去掉直流分量functiony=kexipu(m,n)%由数据量为n的高斯白噪声产生向量为n，功率谱为柯西谱的高斯随机向量wc=2*pi*256;T0=1/(256*m);x=gaussian(n);y=zeros(1,n);y(1)=wc*T0*x(1);fori=2:ny(i)=wc*T0*x(i)+exp(-wc*T0)*y(i-1);endb=canshu(y);%y=y-b(1);%去掉直流分量y=conv(y,y);y=fft(y);y=abs(y);i=1:2*n-1;plot(i,y)functionplotpu(x)%绘出随机数的功率谱密度函数频域的图形。%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%w=fft(x);w=abs(w);v=2*pi/length(w);i=0:v:(2*pi-v);plot(i,w);三.雷达系统仿真function[t,s,g,f0,fs,f1]=huibo%产生目标回波信号x,系统噪声y，地物杂波z以及回波p%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%f0=3*10^7;%发射信号频率w=0;%发射信号初始相位c=3*10^8;%光速l=c/f0;%雷达信号波长(载波波长)R=40